Triple
T18747334
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Elkanah |
E458436
|
entity |
| Predicate | comforted |
P12480
|
FINISHED |
| Object | Hannah in her barrenness |
—
|
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: Hannah in her barrenness | Statement: [Elkanah, comforted, Hannah in her barrenness]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: comforted Context triple: [Elkanah, comforted, Hannah in her barrenness]
-
A.
relativeComfort
Indicates a comparative relationship where one entity is judged to be more or less comfortable than another under given conditions.
-
B.
relievedBy
chosen
Indicates that one entity eases, reduces, or removes the burden, pain, stress, or responsibility experienced by another entity.
-
C.
relief
Indicates a state or action in which distress, pain, or difficulty is reduced, eased, or removed for an entity.
-
D.
compensated
Indicates that one entity provides payment or some form of recompense to another entity in return for goods, services, or loss incurred.
-
E.
appeases
Indicates an action where one entity calms, placates, or satisfies another entity to reduce anger, tension, or hostility.
- 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_69d8d394dc308190b6725073f5db324c |
completed | April 10, 2026, 10:40 a.m. |
| NER | Named-entity recognition | batch_69e576936cf08190b3c0d2f4e8a616fc |
completed | April 20, 2026, 12:42 a.m. |
| PD | Predicate disambiguation | batch_69e48d03766c8190a43f7681842f4f8d |
completed | April 19, 2026, 8:06 a.m. |
Created at: April 10, 2026, 11:51 a.m.