Triple
T5577082
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | 9-1-1 |
E146345
|
entity |
| Predicate | mainCharacter |
P1183
|
FINISHED |
| Object |
Howard Han
Howard "Chimney" Han is a central character on the television drama series "9-1-1," known as a dedicated and resourceful firefighter-paramedic with a complex personal history.
|
E528705
|
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: Howard Han | Statement: [9-1-1, mainCharacter, Howard Han]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Howard Han Context triple: [9-1-1, mainCharacter, Howard Han]
-
A.
Doug J. Hannah
Doug J. Hannah is a film editor best known for his work on the science fiction thriller "The Cloverfield Paradox."
-
B.
Ron Hagen
Ron Hagen is a cinematographer best known for his work on the Australian film "Romper Stomper."
-
C.
Howard Pine
Howard Pine was a film producer active in mid-20th-century American cinema.
-
D.
Lew Hahn
Lew Hahn is a recording engineer known for his work on notable music projects such as the song "I'm Every Woman."
-
E.
Dick Hantak
Dick Hantak is a former National Football League official best known for serving as the referee in Super Bowl XXVII.
- 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: Howard Han Triple: [9-1-1, mainCharacter, Howard Han]
Generated description
Howard "Chimney" Han is a central character on the television drama series "9-1-1," known as a dedicated and resourceful firefighter-paramedic with a complex personal history.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Howard Han Target entity description: Howard "Chimney" Han is a central character on the television drama series "9-1-1," known as a dedicated and resourceful firefighter-paramedic with a complex personal history.
-
A.
Doug J. Hannah
Doug J. Hannah is a film editor best known for his work on the science fiction thriller "The Cloverfield Paradox."
-
B.
Ron Hagen
Ron Hagen is a cinematographer best known for his work on the Australian film "Romper Stomper."
-
C.
Howard Pine
Howard Pine was a film producer active in mid-20th-century American cinema.
-
D.
Lew Hahn
Lew Hahn is a recording engineer known for his work on notable music projects such as the song "I'm Every Woman."
-
E.
Dick Hantak
Dick Hantak is a former National Football League official best known for serving as the referee in Super Bowl XXVII.
- 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_69c008ffed108190a084602227af6157 |
completed | March 22, 2026, 3:21 p.m. |
| NER | Named-entity recognition | batch_69c020697fbc8190bd084d7896db3ab8 |
completed | March 22, 2026, 5:01 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69c02855acac8190bd00219aa9647e98 |
completed | March 22, 2026, 5:35 p.m. |
| NEDg | Description generation | batch_69c0366f37f0819097ca1b23b8ebecc2 |
completed | March 22, 2026, 6:35 p.m. |
| NED2 | Entity disambiguation (via description) | batch_69c036ee4e1c8190b9e60655d72407ff |
completed | March 22, 2026, 6:37 p.m. |
Created at: March 22, 2026, 3:37 p.m.