Triple
T3071014
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Home Run Derby |
E64020
|
entity |
| Predicate | previousSponsor |
P17776
|
FINISHED |
| Object | Gillette |
E24830
|
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: Gillette | Statement: [Home Run Derby, previousSponsor, Gillette]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Gillette Context triple: [Home Run Derby, previousSponsor, Gillette]
-
A.
Gillette
chosen
Gillette is a globally recognized American brand best known for its razors and shaving products.
-
B.
Braun
Braun is a German surname most infamously associated with Eva Braun, the longtime companion and brief wife of Adolf Hitler.
-
C.
Colgate-Palmolive
Colgate-Palmolive is a global consumer products company best known for its oral care, personal care, home care, and pet nutrition brands.
-
D.
Lifebuoy
Lifebuoy is a long-established global soap and hygiene brand known for its antibacterial products and health-focused marketing.
-
E.
Procter & Gamble
Procter & Gamble is a multinational consumer goods corporation known for a wide range of household, personal care, and hygiene brands sold globally.
- 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_69ad857a8aec8190bfdfd9c14554ac5a |
completed | March 8, 2026, 2:19 p.m. |
| NER | Named-entity recognition | batch_69ada14b366881908e2ca104e5f38251 |
completed | March 8, 2026, 4:18 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69b1f87f6a3881908ae313f62ff13159 |
completed | March 11, 2026, 11:19 p.m. |
Created at: March 8, 2026, 3:02 p.m.