Triple
T8651087
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Patton Oswalt |
E205099
|
entity |
| Predicate | notableWork |
P4
|
FINISHED |
| Object |
Big Fan
Big Fan is a dark comedy-drama film about an obsessive New York Giants fan whose life unravels after a violent encounter with his favorite player.
|
E749718
|
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: Big Fan | Statement: [Patton Oswalt, notableWork, Big Fan]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Big Fan Context triple: [Patton Oswalt, notableWork, Big Fan]
-
A.
The Fan
The Fan is a 1996 psychological thriller film about an obsessive baseball fan whose fixation on his favorite player turns dangerously violent.
-
B.
The Fan
The Fan is the popular nickname for Beijing's National Indoor Stadium, a major multi-purpose arena known for hosting events during the 2008 and 2022 Olympic Games.
-
C.
Fan y Big
Fan y Big is a prominent peak in the central Brecon Beacons of South Wales, known for its distinctive cliffs and panoramic views.
-
D.
Fanatikerne
Fanatikerne is a notable painting by Norwegian artist Adolph Tidemand depicting religious zealots in a dramatic, realist style.
-
E.
Super Star
Super Star is a powerful, temporary invincibility-granting item in the Super Mario video game series that lets characters defeat enemies by simply touching them.
- 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: Big Fan Triple: [Patton Oswalt, notableWork, Big Fan]
Generated description
Big Fan is a dark comedy-drama film about an obsessive New York Giants fan whose life unravels after a violent encounter with his favorite player.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Big Fan Target entity description: Big Fan is a dark comedy-drama film about an obsessive New York Giants fan whose life unravels after a violent encounter with his favorite player.
-
A.
The Fan
The Fan is a 1996 psychological thriller film about an obsessive baseball fan whose fixation on his favorite player turns dangerously violent.
-
B.
The Fan
The Fan is the popular nickname for Beijing's National Indoor Stadium, a major multi-purpose arena known for hosting events during the 2008 and 2022 Olympic Games.
-
C.
Fan y Big
Fan y Big is a prominent peak in the central Brecon Beacons of South Wales, known for its distinctive cliffs and panoramic views.
-
D.
Fanatikerne
Fanatikerne is a notable painting by Norwegian artist Adolph Tidemand depicting religious zealots in a dramatic, realist style.
-
E.
Super Star
Super Star is a powerful, temporary invincibility-granting item in the Super Mario video game series that lets characters defeat enemies by simply touching them.
- 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_69ca834e56848190abb0eeaec9dedd32 |
completed | March 30, 2026, 2:06 p.m. |
| NER | Named-entity recognition | batch_69cc48150e6c8190a7a3b92b4b640858 |
completed | March 31, 2026, 10:17 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69ceccc95b588190b5e44c73cf93d18b |
completed | April 2, 2026, 8:08 p.m. |
| NEDg | Description generation | batch_69cece1681288190a6c99407bc2f0bdd |
completed | April 2, 2026, 8:14 p.m. |
| NED2 | Entity disambiguation (via description) | batch_69cecec118ac81909fbcafe841354c32 |
completed | April 2, 2026, 8:17 p.m. |
Created at: March 30, 2026, 6:29 p.m.