Triple
T12010659
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Allied headquarters in Reims |
E285894
|
entity |
| Predicate | languageOfSignatures |
P102646
|
FINISHED |
| Object | English |
—
|
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: English | Statement: [Allied headquarters in Reims, languageOfSignatures, English]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: languageOfSignatures Context triple: [Allied headquarters in Reims, languageOfSignatures, English]
-
A.
languageOfSignage
Indicates the language used on signs or written displays associated with an entity.
-
B.
signatureLanguage
Indicates the language in which a signature (e.g., on a document or agreement) is written or expressed.
-
C.
hasAdditionalLanguageOfSignage
Indicates that an entity has signage presented in one or more additional languages beyond the primary language used.
-
D.
tertiaryLanguageOfSignage
Indicates that a language is used as the third-most prominent language on signage in a given context or location.
-
E.
languageOfLetters
Indicates that one entity is the language in which the other entity’s letters or written correspondence are composed.
- F. None of above. chosen
Provenance (4 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_69d6ab45a368819084fce08bf0dc3705 |
completed | April 8, 2026, 7:23 p.m. |
| NER | Named-entity recognition | batch_69d903d7777481908cd5a001f75e2ee3 |
completed | April 10, 2026, 2:06 p.m. |
| PD | Predicate disambiguation | batch_69d902b245cc8190af96a9c2bd9c6250 |
completed | April 10, 2026, 2:01 p.m. |
| PDg | Predicate description generation | batch_69d9038e39f881908c58c19802ba2eb0 |
completed | April 10, 2026, 2:05 p.m. |
Created at: April 8, 2026, 9:46 p.m.