Triple
T35991800
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Alexis Pugh |
E1040865
|
entity |
| Predicate | hasTheaterNamedAfter |
P138265
|
FINISHED |
| Object | Alexis & Jim Pugh Theater |
—
|
NE NERFINISHED |
How this triple was built (2 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: Alexis & Jim Pugh Theater | Statement: [Alexis Pugh, hasTheaterNamedAfter, Alexis & Jim Pugh Theater]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasTheaterNamedAfter Context triple: [Alexis Pugh, hasTheaterNamedAfter, Alexis & Jim Pugh Theater]
-
A.
theatreNamedAfter
chosen
Indicates that a theatre bears the name of a particular person, place, or entity in whose honor or reference it is named.
-
B.
hasParkNamedAfter
Indicates that one entity has a park that is named in honor of, or after, another entity.
-
C.
hasPlaceNamedAfter
Indicates that one place is named in honor of or derived from the name of another place.
-
D.
hasTheatreDistrictRole
Indicates that an entity holds a specific role, function, or designation within a theatre district.
-
E.
hasAmphitheaterName
Indicates that an entity (such as a venue or site) bears a specific name identifying it as an amphitheater.
- F. None of above.
Provenance (3 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_69f76e29084c819083987b828d414de7 |
completed | May 3, 2026, 3:47 p.m. |
| NER | Named-entity recognition | batch_69f7bbf906d8819099020e548dd56bc9 |
completed | May 3, 2026, 9:19 p.m. |
| PD | Predicate disambiguation | batch_69f7b9a2dcf88190a7c9e109e41267be |
completed | May 3, 2026, 9:09 p.m. |
Created at: May 3, 2026, 4:07 p.m.