Triple
T967647
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Hesiodic Catalogue of Women |
E20872
|
entity |
| Predicate | survivesAs |
P22266
|
FINISHED |
| Object | papyrus fragments |
—
|
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: papyrus fragments | Statement: [Hesiodic Catalogue of Women, survivesAs, papyrus fragments]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: survivesAs Context triple: [Hesiodic Catalogue of Women, survivesAs, papyrus fragments]
-
A.
survivingStructure
Indicates that a structure continues to exist or remain intact after a potentially destructive event or over a significant period of time.
-
B.
hasSurvivors
Indicates that one or more entities continue to exist or remain alive after a particular event, condition, or incident.
-
C.
survivedEvent
Indicates that an entity continued to live or exist after experiencing and not being destroyed or killed by a particular event.
-
D.
survivorTerm
Indicates that one entity is designated as the surviving or remaining party in relation to another entity, often after a loss, termination, or adverse event.
-
E.
hasSurvivorTerm
Indicates that an entity is associated with a term or label specifically used to describe survivors of an event, condition, or circumstance.
- 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_69a493b33d2c81909c52c369d3ca8436 |
completed | March 1, 2026, 7:29 p.m. |
| NER | Named-entity recognition | batch_69a4b43549008190a4d65efdc3bda520 |
completed | March 1, 2026, 9:48 p.m. |
| PD | Predicate disambiguation | batch_69a4b2a42c1481908d940cbe0aefdd3b |
completed | March 1, 2026, 9:41 p.m. |
| PDg | Predicate description generation | batch_69a4b36064a48190b85c402f32cbadd1 |
completed | March 1, 2026, 9:45 p.m. |
Created at: March 1, 2026, 7:40 p.m.