Triple
T14065291
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Héctor Rivera |
E338453
|
entity |
| Predicate | relationshipToMiguel |
P112679
|
FINISHED |
| Object | great-great-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: great-great-grandfather | Statement: [Héctor Rivera, relationshipToMiguel, great-great-grandfather]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: relationshipToMiguel Context triple: [Héctor Rivera, relationshipToMiguel, great-great-grandfather]
-
A.
relationshipStatusWithMichael
Indicates the type or state of the relationship that an entity currently has with Michael.
-
B.
relationshipToTony
Indicates the specific type of relationship or connection that an entity has with Tony.
-
C.
relationToDominicanFamily
Indicates a familial or kinship relationship that a person has with a Dominican family.
-
D.
relationshipToCalaf
Indicates the specific type of personal or social relationship an entity has with Calaf.
-
E.
relationshipToHenry
Indicates the specific type of relationship or connection that an entity has to Henry.
- 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_69d81c67ba6c819091935650dfb3b895 |
completed | April 9, 2026, 9:38 p.m. |
| NER | Named-entity recognition | batch_69de5689c7f48190a47ca94eaa8a9ef9 |
completed | April 14, 2026, 3 p.m. |
| PD | Predicate disambiguation | batch_69de05adef888190b023ab42ef5076b6 |
completed | April 14, 2026, 9:15 a.m. |
| PDg | Predicate description generation | batch_69de2398856c81908bed6070e4ca6ab1 |
completed | April 14, 2026, 11:23 a.m. |
Created at: April 9, 2026, 10:21 p.m.