Triple
T14116367
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Tide |
E339785
|
entity |
| Predicate | competitor |
P1375
|
FINISHED |
| Object | Gain |
E339787
|
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: Gain | Statement: [Tide, competitor, Gain]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Gain Context triple: [Tide, competitor, Gain]
-
A.
Gain
chosen
Gain is a popular Procter & Gamble laundry detergent brand known for its strong, long-lasting fragrances.
-
B.
Grab
Grab is a Southeast Asian super-app company best known for its ride-hailing, food delivery, and digital payments services.
-
C.
Gap
Gap is a town in southeastern France, known as the capital of the Hautes-Alpes department and a gateway to the French Alps.
-
D.
Gap
Gap is a major American clothing and accessories retailer known for its casual, minimalist style and global high-street presence.
-
E.
Winning
"Winning" is a popular rock song by Santana, known for its uplifting lyrics and melodic guitar-driven sound.
- 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_69d81c6a95b481909e39111e0c1f31ee |
completed | April 9, 2026, 9:38 p.m. |
| NER | Named-entity recognition | batch_69de6010a03c81909f5f160f8d1fa8fa |
completed | April 14, 2026, 3:41 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69fcdf0641008190b88efacc02ba5314 |
completed | May 7, 2026, 6:50 p.m. |
Created at: April 9, 2026, 10:22 p.m.