Triple
T6232870
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Long |
E139397
|
entity |
| Predicate | hasNotableBearer |
P458
|
FINISHED |
| Object |
Hanlong Long
Hanlong Long is an individual notable enough to be recognized as a namesake bearer of the surname Long.
|
E578469
|
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: Hanlong Long | Statement: [Long, hasNotableBearer, Hanlong Long]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Hanlong Long Context triple: [Long, hasNotableBearer, Hanlong Long]
-
A.
Han Lue
Han Lue is a laid-back, skilled street racer and heist crew member in the Fast & Furious franchise, known for his calm demeanor, drifting talent, and constant snacking.
-
B.
Jong Lin
Jong Lin is a Taiwanese cinematographer known for his collaborations with director Ang Lee and his visually rich work on acclaimed international films.
-
C.
He Long
He Long was a prominent Chinese Communist military leader and marshal who played a key role in early revolutionary campaigns and later in the People’s Liberation Army.
-
D.
Younan Xia
Younan Xia is a prominent chemist and materials scientist known for his pioneering work in nanomaterials synthesis and nanotechnology.
-
E.
Shuheng
Shuheng is the given name of He Shuheng, an early Chinese Communist revolutionary and political figure.
- 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: Hanlong Long Triple: [Long, hasNotableBearer, Hanlong Long]
Generated description
Hanlong Long is an individual notable enough to be recognized as a namesake bearer of the surname Long.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Hanlong Long Target entity description: Hanlong Long is an individual notable enough to be recognized as a namesake bearer of the surname Long.
-
A.
Han Lue
Han Lue is a laid-back, skilled street racer and heist crew member in the Fast & Furious franchise, known for his calm demeanor, drifting talent, and constant snacking.
-
B.
Jong Lin
Jong Lin is a Taiwanese cinematographer known for his collaborations with director Ang Lee and his visually rich work on acclaimed international films.
-
C.
He Long
He Long was a prominent Chinese Communist military leader and marshal who played a key role in early revolutionary campaigns and later in the People’s Liberation Army.
-
D.
Younan Xia
Younan Xia is a prominent chemist and materials scientist known for his pioneering work in nanomaterials synthesis and nanotechnology.
-
E.
Shuheng
Shuheng is the given name of He Shuheng, an early Chinese Communist revolutionary and political figure.
- 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_69c008b0e7ac8190808a59573ee646f3 |
completed | March 22, 2026, 3:20 p.m. |
| NER | Named-entity recognition | batch_69c062efa25c8190a54f5a6f5b5ad24f |
completed | March 22, 2026, 9:45 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69c20defd338819099a23d00107c4edd |
completed | March 24, 2026, 4:07 a.m. |
| NEDg | Description generation | batch_69c211c3c60c8190bd5e4f002c1569e0 |
completed | March 24, 2026, 4:23 a.m. |
| NED2 | Entity disambiguation (via description) | batch_69c214b9b83881909da9fedc7ce60f39 |
completed | March 24, 2026, 4:36 a.m. |
Created at: March 22, 2026, 4:22 p.m.