Triple
T5782877
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Coming Home |
E128201
|
entity |
| Predicate | mainCharacter |
P1183
|
FINISHED |
| Object |
Dan Dan
Dan Dan is the central protagonist of the film "Coming Home," whose personal journey and experiences drive the emotional core of the story.
|
E543515
|
NE FINISHED |
How this triple was built (4 steps)
Every LLM step that produced this triple, in pipeline order — named-entity classification, the disambiguation choices (the exact options shown, with the pick highlighted), and the generated description. The batch + timestamp of each is in the Provenance table below.
NER
Named-entity recognition
gpt-5-mini
Instruction
Given a phrase, classify it is english named entity (e.g., persons, organizations, works of art) in Latin script, or not (e.g., literals, dates, URLs, verbose phrases). For disambiguation, the statement where the phrase occurs as object is also given. Please return a JSON object with `phrase` (string, the phrase being analyzed) and `is_ne` (boolean, indicating whether the phrase is a Named Entity).
Input
Phrase: Dan Dan | Statement: [Coming Home, mainCharacter, Dan Dan]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Dan Dan Context triple: [Coming Home, mainCharacter, Dan Dan]
-
A.
Daksum
Daksum is a scenic hill station and forested valley in Jammu and Kashmir, India, known for its lush landscapes, trout-filled streams, and trekking routes in the Anantnag region.
-
B.
Din Da Da
"Din Da Da" is a percussive, chant-driven electro track originally by George Kranz that has been widely sampled and covered in hip-hop and dance music.
-
C.
Ramenki
Ramenki is a Moscow Metro station serving the Kalininsko–Solntsevskaya Line in the Ramenki District of western Moscow, Russia.
-
D.
Maoke Plate
The Maoke Plate is a minor tectonic plate in the region of New Guinea, contributing to the complex and active plate boundary interactions in eastern Indonesia.
-
E.
Oshiage
Oshiage is a district in Sumida, Tokyo, best known as the location of the Tokyo Skytree and its surrounding commercial complex.
- F. None of above. chosen
- G. Unsure - the case is ambiguous/there is not enough information to decide.
NEDg
Description generation
gpt-5.1
Instruction
Generate a one-sentence description of the target entity. You are given a context triple in the form (subject, predicate, object), where the object is the target entity. # Instructions Use the triple to infer relevant information about the entity. Describe the entity based on what is most defining, well-known. Avoid repeating the information from the triple, unless really essential. # Response Format Return only the sentence: "Description: [one-sentence description of the target entity]"
Input
Entity: Dan Dan Triple: [Coming Home, mainCharacter, Dan Dan]
Generated description
Dan Dan is the central protagonist of the film "Coming Home," whose personal journey and experiences drive the emotional core of the story.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Dan Dan Target entity description: Dan Dan is the central protagonist of the film "Coming Home," whose personal journey and experiences drive the emotional core of the story.
-
A.
Daksum
Daksum is a scenic hill station and forested valley in Jammu and Kashmir, India, known for its lush landscapes, trout-filled streams, and trekking routes in the Anantnag region.
-
B.
Din Da Da
"Din Da Da" is a percussive, chant-driven electro track originally by George Kranz that has been widely sampled and covered in hip-hop and dance music.
-
C.
Ramenki
Ramenki is a Moscow Metro station serving the Kalininsko–Solntsevskaya Line in the Ramenki District of western Moscow, Russia.
-
D.
Maoke Plate
The Maoke Plate is a minor tectonic plate in the region of New Guinea, contributing to the complex and active plate boundary interactions in eastern Indonesia.
-
E.
Oshiage
Oshiage is a district in Sumida, Tokyo, best known as the location of the Tokyo Skytree and its surrounding commercial complex.
- F. None of above. chosen
Provenance (5 batches)
The batch behind each pipeline step, in order, with when it ran. Timestamps are batch-level — stages were processed in waves, so the object chain (NER → NED1 → NEDg → NED2) reads in order, but predicate / elicitation batches can sit in a different wave.
| Step | Stage | Batch ID | Status | When |
|---|---|---|---|---|
| creating | Elicitation | batch_69c0084450048190bc647b649a05136b |
completed | March 22, 2026, 3:18 p.m. |
| NER | Named-entity recognition | batch_69c02a184870819084251554eae1e33c |
completed | March 22, 2026, 5:42 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69c07e7a1cb88190980e0cf675aaa906 |
completed | March 22, 2026, 11:42 p.m. |
| NEDg | Description generation | batch_69c086b2f5888190a986efaf948b25fb |
completed | March 23, 2026, 12:17 a.m. |
| NED2 | Entity disambiguation (via description) | batch_69c087493f808190bec82872e44af85c |
completed | March 23, 2026, 12:20 a.m. |
Created at: March 22, 2026, 3:50 p.m.