Triple
T9783405
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Alltech Arena |
E237431
|
entity |
| Predicate | sponsor |
P67
|
FINISHED |
| Object | Alltech |
E822041
|
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: Alltech | Statement: [Alltech Arena, sponsor, Alltech]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Alltech Context triple: [Alltech Arena, sponsor, Alltech]
-
A.
Alltech
chosen
Alltech is a global animal health and nutrition company specializing in feed additives, agricultural biotechnology, and sustainable farming solutions.
-
B.
DowDuPont
DowDuPont was a large American chemical conglomerate formed by the merger of Dow Chemical and DuPont, later split into three independent companies focused on agriculture, materials science, and specialty products.
-
C.
Corteva
Corteva is an American agricultural chemical and seed company formed as an independent entity after the breakup of DowDuPont.
-
D.
Zoetis
Zoetis is a leading global animal health company that develops, manufactures, and markets medicines, vaccines, and diagnostic products for livestock and companion animals.
-
E.
Ventris
Ventris is the surname of Michael Ventris, the British architect and linguist renowned for deciphering the ancient script Linear B.
- 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_69ca84da927881909bda80caecad6010 |
completed | March 30, 2026, 2:12 p.m. |
| NER | Named-entity recognition | batch_69cda1b7740c8190bfb4997eb683d78a |
completed | April 1, 2026, 10:52 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69d1cc4bb6008190b5111d42ceef52b7 |
completed | April 5, 2026, 2:43 a.m. |
Created at: March 30, 2026, 8:27 p.m.