Triple
T37425433
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Tah-gah-jute |
E929974
|
entity |
| Predicate | spouseKilledIn |
P193229
|
FINISHED |
| Object | Yellow Creek massacre |
—
|
NE NERFINISHED |
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: Yellow Creek massacre | Statement: [Tah-gah-jute, spouseKilledIn, Yellow Creek massacre]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: spouseKilledIn Context triple: [Tah-gah-jute, spouseKilledIn, Yellow Creek massacre]
-
A.
spouseAssassinated
Indicates that one person's spouse was deliberately killed by another person.
-
B.
spouseExecuted
Indicates that one person’s spouse was put to death, typically as a result of a legal or extrajudicial execution.
-
C.
spouseExecutedFor
Indicates that one person’s spouse was put to death, typically as a result of a legal or punitive execution.
-
D.
hasVictimSpouse
Indicates that a person’s spouse is the victim in a harmful, criminal, or adverse event involving that person.
-
E.
familyKilledIn
chosen
Indicates that a person's family members were killed in a specified event, location, or incident.
- 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_69f76ebf0f288190ba198a78341613b8 |
completed | May 3, 2026, 3:50 p.m. |
| NER | Named-entity recognition | batch_69feb8e856d48190aa34ad8ee8376e1c |
completed | May 9, 2026, 4:32 a.m. |
| PD | Predicate disambiguation | batch_69feb82a2b6c8190a473cc25976897be |
completed | May 9, 2026, 4:29 a.m. |
Created at: May 3, 2026, 4:16 p.m.