Triple
T5469920
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Erymanthian Boar |
E122804
|
entity |
| Predicate | reactionProvoked |
P52747
|
FINISHED |
| Object | Eurystheus hid in a storage jar |
—
|
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: Eurystheus hid in a storage jar | Statement: [Erymanthian Boar, reactionProvoked, Eurystheus hid in a storage jar]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: reactionProvoked Context triple: [Erymanthian Boar, reactionProvoked, Eurystheus hid in a storage jar]
-
A.
reaction
Indicates a chemical or physical process in which one set of substances or conditions transforms into another, often involving interaction, change, or response between entities.
-
B.
emotionEffect
chosen
Indicates that one entity’s emotional state causes or influences a change in another entity’s feelings, behavior, or condition.
-
C.
triggered
Indicates that one entity causes an event, action, or process involving another entity to start or occur.
-
D.
correctsAberration
Indicates that one entity counteracts, fixes, or compensates for an error, flaw, or deviation present in another entity.
-
E.
upset
Indicates that one entity causes another to feel distressed, unhappy, or emotionally disturbed.
- 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_69bd46459ff48190823377457bcf7128 |
completed | March 20, 2026, 1:06 p.m. |
| NER | Named-entity recognition | batch_69bd927c946c8190aef40679199fede3 |
completed | March 20, 2026, 6:31 p.m. |
| PD | Predicate disambiguation | batch_69bd91a370a88190b5d17b8a5387138d |
completed | March 20, 2026, 6:27 p.m. |
Created at: March 20, 2026, 2:09 p.m.