Triple
T14384518
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Haydée |
E356687
|
entity |
| Predicate | relationshipToEdmondDantès |
P114028
|
FINISHED |
| Object | devoted ally |
—
|
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: devoted ally | Statement: [Haydée, relationshipToEdmondDantès, devoted ally]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: relationshipToEdmondDantès Context triple: [Haydée, relationshipToEdmondDantès, devoted ally]
-
A.
relationshipToBaudelaires
Indicates the type of personal or familial connection an entity has to the Baudelaires.
-
B.
relationshipToOdette
Indicates the specific familial, social, or interpersonal connection that an entity has with Odette.
-
C.
relationshipToMontresor
Indicates the specific personal or social connection an entity has to Montresor.
-
D.
relationshipToTinaBordereau
Indicates the specific type of personal or professional relationship an entity has with Tina Bordereau.
-
E.
relationshipToIsabelArcher
Indicates the specific personal or social connection that an entity has to Isabel Archer.
- 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_69d827927c988190ad98bb0360981783 |
completed | April 9, 2026, 10:26 p.m. |
| NER | Named-entity recognition | batch_69de9025cff881908c08224d90d9f750 |
completed | April 14, 2026, 7:06 p.m. |
| PD | Predicate disambiguation | batch_69de2aa024c48190805df6a9d63deb10 |
completed | April 14, 2026, 11:53 a.m. |
| PDg | Predicate description generation | batch_69de2e08b6c08190bb4c929deab236a6 |
completed | April 14, 2026, 12:07 p.m. |
Created at: April 10, 2026, 1:16 a.m.