Triple
T23451307
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Henry of Portugal |
E567786
|
entity |
| Predicate | politicalResultOfDeath |
P129785
|
FINISHED |
| Object | personal union of Portugal and Spain under the Spanish Habsburgs |
—
|
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: personal union of Portugal and Spain under the Spanish Habsburgs | Statement: [Henry of Portugal, politicalResultOfDeath, personal union of Portugal and Spain under the Spanish Habsburgs]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: politicalResultOfDeath Context triple: [Henry of Portugal, politicalResultOfDeath, personal union of Portugal and Spain under the Spanish Habsburgs]
-
A.
politicalOutcomeAfterDeath
chosen
Indicates the political consequences or changes that occur following an individual's death.
-
B.
politicalOutcome
Indicates the result or consequence of a political process, decision, event, or interaction.
-
C.
deathResultedIn
Indicates that one event, action, or condition caused or led directly to a particular death as its outcome.
-
D.
deathResult
Indicates that one event, condition, or action leads to or causes the death of an entity.
-
E.
governmentCasualties
Indicates that members of a government (such as officials, employees, or security forces) were killed, injured, or otherwise became casualties in an event or conflict.
- 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_69e2458b4c888190b1d7998f9862a558 |
completed | April 17, 2026, 2:36 p.m. |
| NER | Named-entity recognition | batch_69f1a64d3e9c8190a2596b067c4f5061 |
completed | April 29, 2026, 6:33 a.m. |
| PD | Predicate disambiguation | batch_69f06201d33481909b5fd7b92d03e658 |
completed | April 28, 2026, 7:30 a.m. |
Created at: April 17, 2026, 5:52 p.m.