Triple
T17271838
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Gerald D. Hines Interests |
E419278
|
entity |
| Predicate | alsoKnownAs |
P39
|
FINISHED |
| Object | Hines |
E419279
|
NE 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: Hines | Statement: [Gerald D. Hines Interests, alsoKnownAs, Hines]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Hines Context triple: [Gerald D. Hines Interests, alsoKnownAs, Hines]
-
A.
Hines
Hines is a surname most famously associated with Earl Hines, the influential American jazz pianist and bandleader.
-
B.
Hines
chosen
Hines is a global real estate investment, development, and management firm known for its portfolio of prominent commercial properties.
-
C.
Hinkle
Hinkle is a surname most notably associated with American actress Marin Hinkle, known for her roles in television and film.
-
D.
Hilson
Hilson is the surname of American singer, songwriter, and actress Keri Hilson, known for her R&B and pop music career.
-
E.
Hoskins
Hoskins is a surname most notably associated with the late English actor Bob Hoskins, renowned for his roles in films such as "Who Framed Roger Rabbit" and "Mona Lisa."
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide.
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_69d886da626481908a14ce7830329a35 |
completed | April 10, 2026, 5:12 a.m. |
| NER | Named-entity recognition | batch_69e42f4a3c4c81908a28c9f8bdf648ca |
completed | April 19, 2026, 1:26 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_6a01794d605481908b5e430c3142c203 |
completed | May 11, 2026, 6:38 a.m. |
Created at: April 10, 2026, 5:40 a.m.