Triple
T33394758
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Al-Ruha |
E855142
|
entity |
| Predicate | correspondsToAncientName |
P20952
|
FINISHED |
| Object | Edessa |
—
|
NE NERFINISHED |
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: Edessa | Statement: [Al-Ruha, correspondsToAncientName, Edessa]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: correspondsToAncientName Context triple: [Al-Ruha, correspondsToAncientName, Edessa]
-
A.
ancientNameOf
chosen
Indicates that one entity is the historical or ancient name by which the other entity was formerly known.
-
B.
hasAncientEthnicName
Indicates that an entity is associated with an ethnic name or designation that originates from ancient times.
-
C.
isAncient
Indicates that the entity existed or originated in a very distant past, typically far earlier than the commonly referenced historical period.
-
D.
isHistoricalName
Indicates that a given name is a former or past designation historically used for an entity.
-
E.
ancientNameOfServedSettlement
Indicates that the object is an earlier or historical name by which the settlement served by the subject was known.
- 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_69f3496e3f1c8190bcecfa82aa9d17ff |
completed | April 30, 2026, 12:22 p.m. |
| NER | Named-entity recognition | batch_69f760a35b988190904e6267553ad2fe |
completed | May 3, 2026, 2:50 p.m. |
| PD | Predicate disambiguation | batch_69f75eb3d6f081908c933474eb359e3d |
completed | May 3, 2026, 2:41 p.m. |
Created at: May 1, 2026, 1:35 a.m.