Triple
T13966258
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Keos |
E335930
|
entity |
| Predicate | hasAlternativeName |
P39
|
FINISHED |
| Object | Zea |
E335931
|
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: Zea | Statement: [Keos, hasAlternativeName, Zea]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Zea Context triple: [Keos, hasAlternativeName, Zea]
-
A.
Zea
chosen
Zea is the former name of Kea, an island in the Cyclades archipelago of Greece known for its traditional villages and scenic landscapes.
-
B.
Zea mays
Zea mays is the domesticated cereal crop commonly known as maize or corn, widely cultivated worldwide for food, feed, and industrial uses.
-
C.
Amaranto
Amaranto is the traditional maroon-colored nickname associated with Italian football club Reggina 1914 and its supporters.
-
D.
Centeno
Centeno is a Portuguese surname most notably associated with Mário Centeno, an economist and former finance minister of Portugal.
-
E.
Sorghum bicolor
Sorghum bicolor is a major cereal crop species grown worldwide for grain, forage, and biofuel, notable for its drought tolerance and importance in food and feed production.
- 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_69d81c61f3508190aaf2ca0dc0002c59 |
completed | April 9, 2026, 9:38 p.m. |
| NER | Named-entity recognition | batch_69de2e8c9e988190a84c9ca8a78b515f |
completed | April 14, 2026, 12:09 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69fba1da70588190a6c9a3895d92be5b |
completed | May 6, 2026, 8:17 p.m. |
Created at: April 9, 2026, 10:18 p.m.