Triple
T174606
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Republic of Texas |
E3548
|
entity |
| Predicate | demiseCause |
P144
|
FINISHED |
| Object | annexation by the United States |
—
|
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: annexation by the United States | Statement: [Republic of Texas, demiseCause, annexation by the United States]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: demiseCause Context triple: [Republic of Texas, demiseCause, annexation by the United States]
-
A.
causeOfDeath
chosen
Indicates the specific factor, event, or condition that directly resulted in an entity’s death.
-
B.
deathToll
Indicates the number of deaths resulting from a particular event, situation, or cause.
-
C.
placeOfDeath
Indicates the location where an entity (typically a person or animal) died.
-
D.
causeOf
Indicates that one entity brings about, produces, or is responsible for the occurrence or existence of another entity or event.
-
E.
mortalityRate
Indicates the proportion of individuals in a defined population that die within a specified time period.
- 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_69a25374990081909766d30c79a18e0e |
completed | Feb. 28, 2026, 2:31 a.m. |
| NER | Named-entity recognition | batch_69a258e32da88190ad9485aecd0bf08f |
completed | Feb. 28, 2026, 2:54 a.m. |
| PD | Predicate disambiguation | batch_69a256689f908190afeb5ee82022a911 |
completed | Feb. 28, 2026, 2:43 a.m. |
Created at: Feb. 28, 2026, 2:39 a.m.