Triple
T36731760
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Philomele |
E907357
|
entity |
| Predicate | mutilatedBy |
P993
|
FINISHED |
| Object | Tereus (cutting out her tongue) |
—
|
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: Tereus (cutting out her tongue) | Statement: [Philomele, mutilatedBy, Tereus (cutting out her tongue)]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: mutilatedBy Context triple: [Philomele, mutilatedBy, Tereus (cutting out her tongue)]
-
A.
dismembered
Indicates that one entity has cut or torn another entity’s body into separate parts, typically removing limbs or sections.
-
B.
sacrificedBy
Indicates that an entity has been given up, killed, or offered as a sacrifice by another entity.
-
C.
blightedBy
Indicates that one entity is negatively affected, damaged, or ruined by another entity or factor.
-
D.
fatallyDamaged
Indicates that an entity has been harmed or impaired to such an extent that death is inevitable or has already occurred as a result of the damage.
-
E.
damagedBy
chosen
Indicates that one entity has caused harm, impairment, or deterioration to another entity.
- 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_69f76e75aa6881909b844d00a3888ee5 |
completed | May 3, 2026, 3:49 p.m. |
| NER | Named-entity recognition | batch_69f7c9f5a8848190ba956ff27f44e396 |
completed | May 3, 2026, 10:19 p.m. |
| PD | Predicate disambiguation | batch_69f7c8999a348190abc1895eaa6e036d |
completed | May 3, 2026, 10:13 p.m. |
Created at: May 3, 2026, 4:12 p.m.