Triple
T5260417
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Anna (wife of Tobit) |
E118808
|
entity |
| Predicate | expressesEmotion |
P4750
|
FINISHED |
| Object | sorrow over Tobit’s blindness |
—
|
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: sorrow over Tobit’s blindness | Statement: [Anna (wife of Tobit), expressesEmotion, sorrow over Tobit’s blindness]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: expressesEmotion Context triple: [Anna (wife of Tobit), expressesEmotion, sorrow over Tobit’s blindness]
-
A.
faceExpression
Indicates the specific facial expression an entity is displaying, capturing its visible emotional or expressive state.
-
B.
feels
Indicates that an entity experiences or has a particular emotion, sensation, or internal state in relation to something.
-
C.
feltIn
Indicates that a sensation, emotion, or effect is experienced within a particular location, context, or entity.
-
D.
emotionEffect
Indicates that one entity’s emotional state causes or influences a change in another entity’s feelings, behavior, or condition.
-
E.
expresses
chosen
Indicates that one entity conveys, communicates, or articulates a thought, feeling, or idea through another medium or form.
- 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_69bd446a42c88190b7ecbef006561d55 |
completed | March 20, 2026, 12:58 p.m. |
| NER | Named-entity recognition | batch_69bd7bcf026c8190881b6e14b962a3c9 |
completed | March 20, 2026, 4:54 p.m. |
| PD | Predicate disambiguation | batch_69bd77c55224819096c0bcfcfae79bd3 |
completed | March 20, 2026, 4:37 p.m. |
Created at: March 20, 2026, 1:50 p.m.