Triple
T26682010
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Yankee Brigade |
E672636
|
entity |
| Predicate | usesRegionalNickname |
P69635
|
FINISHED |
| Object | Yankee |
—
|
LITERAL 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: Yankee | Statement: [Yankee Brigade, usesRegionalNickname, Yankee]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: usesRegionalNickname Context triple: [Yankee Brigade, usesRegionalNickname, Yankee]
-
A.
regionalNickname
chosen
Indicates that one entity is an informal or colloquial name used for another entity within a specific geographic region.
-
B.
touristRegionNickname
Indicates that a tourist region is known by a particular informal or colloquial nickname.
-
C.
regionallyKnownAs
Indicates that an entity is known by a particular name or designation within a specific geographic region.
-
D.
metropolitanAreaNickname
Indicates that a metropolitan area is known by a particular informal or colloquial nickname.
-
E.
hasRegionalName
Indicates that an entity is known by a specific name or designation within a particular region or locality.
- F. None of above.
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_69eecda13424819092b17942c4edf722 |
completed | April 27, 2026, 2:44 a.m. |
| NER | Named-entity recognition | batch_69f6352fdb788190b9bad30243690743 |
completed | May 2, 2026, 5:32 p.m. |
| PD | Predicate disambiguation | batch_69f631850ae08190a0ba51e4f1e4ccb3 |
completed | May 2, 2026, 5:16 p.m. |
Created at: April 27, 2026, 3:20 a.m.