Triple
T1810469
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Berytus |
E40318
|
entity |
| Predicate | hadLanguage |
P28976
|
FINISHED |
| Object | Phoenician |
—
|
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: Phoenician | Statement: [Berytus, hadLanguage, Phoenician]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hadLanguage Context triple: [Berytus, hadLanguage, Phoenician]
-
A.
hasLanguageOn
Indicates that an entity uses or is associated with a particular language in a specific context, medium, or location.
-
B.
hasLanguageStatus
Indicates that an entity has a particular status or condition regarding its language use, recognition, or classification.
-
C.
hasProtoLanguage
Indicates that a language or language family originates from, or is derived from, a specified proto-language.
-
D.
formerLanguage
chosen
Indicates that one entity was previously the language of another entity but is no longer in that role.
-
E.
hasLanguageEvidenceOf
Indicates that there is linguistic or textual evidence supporting, documenting, or attesting to the related entity or claim.
- 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_69a88643a3388190a612f2ebe1fb29e7 |
completed | March 4, 2026, 7:21 p.m. |
| NER | Named-entity recognition | batch_69ab694d75ac8190a4d61399c04b9fb9 |
completed | March 6, 2026, 11:54 p.m. |
| PD | Predicate disambiguation | batch_69aa61d6b8ec8190a1597b2e44ea6534 |
completed | March 6, 2026, 5:10 a.m. |
Created at: March 4, 2026, 7:32 p.m.