Triple
T11524143
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Chris Brinker |
E273245
|
entity |
| Predicate | familyName |
P18
|
FINISHED |
| Object | Brinker |
E103633
|
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: Brinker | Statement: [Chris Brinker, familyName, Brinker]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Brinker Context triple: [Chris Brinker, familyName, Brinker]
-
A.
Brinker
chosen
Brinker is the surname of Nancy Goodman Brinker, the American businesswoman and philanthropist who founded the Susan G. Komen breast cancer organization.
-
B.
Brinker International
Brinker International is a major American restaurant company best known as the parent of casual dining chains such as Chili’s Grill & Bar and Maggiano’s Little Italy.
-
C.
Richter’s Burger Co.
Richter’s Burger Co. is a quick-service burger restaurant at Universal Studios Florida themed around an earthquake-ravaged San Francisco waterfront.
-
D.
Hillenbrand
Hillenbrand is a surname of German origin borne by various notable individuals in fields such as diplomacy, literature, and sports.
-
E.
Spreckels
Spreckels is a prominent American family name historically associated with major sugar industry enterprises and philanthropy, particularly in California.
- 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_69d6aae3fbec8190a14632a5df2538b6 |
completed | April 8, 2026, 7:22 p.m. |
| NER | Named-entity recognition | batch_69d87fd26648819083de19bcddf8ad69 |
completed | April 10, 2026, 4:42 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69e62562efb88190bbf3c7bbec8233aa |
completed | April 20, 2026, 1:08 p.m. |
Created at: April 8, 2026, 9:37 p.m.