Triple
T14744583
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Tisch family |
E346433
|
entity |
| Predicate | roleInLoewsCorporation |
P115610
|
FINISHED |
| Object | controlling shareholders |
—
|
LITERAL FINISHED |
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: controlling shareholders | Statement: [Tisch family, roleInLoewsCorporation, controlling shareholders]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: roleInLoewsCorporation Context triple: [Tisch family, roleInLoewsCorporation, controlling shareholders]
-
A.
roleInCinerama
Indicates that an entity has a role or participation in a Cinerama film or production.
-
B.
roleInLasVegas
Indicates that an entity holds or held a specific role, position, or function within the context of Las Vegas (such as in its government, organizations, events, or productions).
-
C.
roleInLanternEntertainment
Indicates that an entity holds or held a specific role or position within Lantern Entertainment.
-
D.
roleInAttraction
Indicates the specific function or position an entity holds within the context of a particular attraction or point of interest.
-
E.
hasTheatreDistrictRole
Indicates that an entity holds a specific role, function, or designation within a theatre district.
- F. None of above. chosen
Provenance (4 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_69d822e6f1c88190bc494d491a907114 |
completed | April 9, 2026, 10:06 p.m. |
| NER | Named-entity recognition | batch_69dec7d002708190a32a4a45e96fc389 |
completed | April 14, 2026, 11:03 p.m. |
| PD | Predicate disambiguation | batch_69de8bf9331481909582045cd567d91f |
completed | April 14, 2026, 6:48 p.m. |
| PDg | Predicate description generation | batch_69de8f4b67cc8190b84b59fcec5cf579 |
completed | April 14, 2026, 7:02 p.m. |
Created at: April 10, 2026, 1:30 a.m.