Triple
T37544086
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Οἰνόμαος |
E933406
|
entity |
| Predicate | numberOfSuitorsKilled |
P205972
|
FINISHED |
| Object | many (traditionally 13 or more) |
—
|
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: many (traditionally 13 or more) | Statement: [Οἰνόμαος, numberOfSuitorsKilled, many (traditionally 13 or more)]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: numberOfSuitorsKilled Context triple: [Οἰνόμαος, numberOfSuitorsKilled, many (traditionally 13 or more)]
-
A.
numberOfHusbandsKilled
Indicates the count of husbands that an entity has killed.
-
B.
numberOfPerpetratorsKilled
Indicates the count of perpetrators who were killed in the context of the described event or incident.
-
C.
hasSuitors
Indicates that an entity is the object of romantic or marital interest from one or more other entities.
-
D.
hasLoverVictim
Indicates that an entity has, as a lover or romantic partner, another entity who is also the victim in a relevant event or situation.
-
E.
numberOfPriestsKilled
Indicates the quantity of priests who were killed in a given event or context.
- 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_69f76ec999288190ae26ec7b6aea7046 |
completed | May 3, 2026, 3:50 p.m. |
| NER | Named-entity recognition | batch_6a037cad051c8190b28b354b89208574 |
completed | May 12, 2026, 7:17 p.m. |
| PD | Predicate disambiguation | batch_6a037a1553e08190bb7424c448cb1f33 |
completed | May 12, 2026, 7:05 p.m. |
| PDg | Predicate description generation | batch_6a037c842b2c819082f1d2db995ac2eb |
completed | May 12, 2026, 7:16 p.m. |
Created at: May 3, 2026, 4:17 p.m.