Triple
T5957473
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Antipater of Sidon |
E132551
|
entity |
| Predicate | hasPartOfCorpus |
P67055
|
FINISHED |
| Object | funerary epigrams |
—
|
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: funerary epigrams | Statement: [Antipater of Sidon, hasPartOfCorpus, funerary epigrams]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasPartOfCorpus Context triple: [Antipater of Sidon, hasPartOfCorpus, funerary epigrams]
-
A.
hasNotableCorpus
Indicates that an entity possesses a significant, well-recognized body of work, texts, or collected materials associated with it.
-
B.
corpus
Indicates that an entity is a collection or body of texts, documents, or linguistic data used as a unified set for analysis or reference.
-
C.
hasLimitedCorpus
Indicates that the associated entity possesses only a small or restricted set of available data, texts, or examples for use or analysis.
-
D.
hasCorpusType
Indicates the type or category of corpus associated with an entity (e.g., text, speech, multimodal).
-
E.
hasPartIn
Indicates that an entity participates in or plays a role within a larger event, process, or composite entity.
- 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_69c0086b05cc8190a8f36a96927a525c |
completed | March 22, 2026, 3:19 p.m. |
| NER | Named-entity recognition | batch_69c03fb7f8a88190a8bd45208bda4a03 |
completed | March 22, 2026, 7:15 p.m. |
| PD | Predicate disambiguation | batch_69c0335a635881909c58c1ef0f97f1e8 |
completed | March 22, 2026, 6:22 p.m. |
| PDg | Predicate description generation | batch_69c03fb6bb7c81909c5629fba408dc69 |
completed | March 22, 2026, 7:15 p.m. |
Created at: March 22, 2026, 4:02 p.m.