Triple
T22394454
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Monsieur Gillenormand |
E553593
|
entity |
| Predicate | relationshipToMariusPontmercy |
P147485
|
FINISHED |
| Object | grandfather |
—
|
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: grandfather | Statement: [Monsieur Gillenormand, relationshipToMariusPontmercy, grandfather]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: relationshipToMariusPontmercy Context triple: [Monsieur Gillenormand, relationshipToMariusPontmercy, grandfather]
-
A.
relationshipToJeanValjean
Indicates the specific interpersonal or social connection that an entity has to Jean Valjean.
-
B.
relationshipStatusWithFantine
Indicates the type or state of the relationship that an entity currently has with Fantine.
-
C.
relationshipToBaudelaires
Indicates the type of personal or familial connection an entity has to the Baudelaires.
-
D.
relationshipToMariane
Indicates the specific type of relationship or connection that an entity has to Mariane.
-
E.
relationshipToGoriot
Indicates the type or nature of a person's relationship to Goriot.
- 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_69e11e4cf87c8190a1ff474daec326b7 |
completed | April 16, 2026, 5:37 p.m. |
| NER | Named-entity recognition | batch_69f1585dac3c8190bc221f35b3eefa3f |
completed | April 29, 2026, 1:01 a.m. |
| PD | Predicate disambiguation | batch_69e73015484c8190a9a0b9f554b61a81 |
completed | April 21, 2026, 8:06 a.m. |
| PDg | Predicate description generation | batch_69e73597b51c8190aeff27f4779b82f3 |
completed | April 21, 2026, 8:30 a.m. |
Created at: April 16, 2026, 8:45 p.m.