Triple
T8706411
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Angelica Schuyler Church |
E206662
|
entity |
| Predicate | relationshipToAlexanderHamilton |
P7844
|
FINISHED |
| Object | sister-in-law |
—
|
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: sister-in-law | Statement: [Angelica Schuyler Church, relationshipToAlexanderHamilton, sister-in-law]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: relationshipToAlexanderHamilton Context triple: [Angelica Schuyler Church, relationshipToAlexanderHamilton, sister-in-law]
-
A.
historicalRelationship
Indicates a relationship that existed between entities in the past, often tied to a specific historical period, context, or event.
-
B.
hasPoliticalRelationshipWith
Indicates a political connection or association between two entities, such as alliances, rivalries, collaborations, or other forms of political interaction.
-
C.
relationshipToMorganAlexander
Indicates the specific type of relationship or connection an entity has to Morgan Alexander.
-
D.
hasFamilialTieTo
chosen
Indicates a relationship where two entities are connected by family bonds, such as by blood, marriage, or adoption.
-
E.
relativeTypeToNapoleonBonaparte
Indicates the specific familial relationship that an entity has to Napoleon Bonaparte.
- 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_69ca835645e881908f00e3c8b51da81d |
completed | March 30, 2026, 2:06 p.m. |
| NER | Named-entity recognition | batch_69cc58fcac748190a82b57aeb7c43df9 |
completed | March 31, 2026, 11:30 p.m. |
| PD | Predicate disambiguation | batch_69cc456bda508190a9aa0fb92760739e |
completed | March 31, 2026, 10:06 p.m. |
Created at: March 30, 2026, 6:35 p.m.