Triple
T26687944
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Battle of Dun Nechtain |
E672797
|
entity |
| Predicate | outcomeForNorthumbria |
P164290
|
FINISHED |
| Object | loss of king and army |
—
|
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: loss of king and army | Statement: [Battle of Dun Nechtain, outcomeForNorthumbria, loss of king and army]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: outcomeForNorthumbria Context triple: [Battle of Dun Nechtain, outcomeForNorthumbria, loss of king and army]
-
A.
outcomeForUnitedKingdom
Indicates the result, consequence, or impact that something has specifically for the United Kingdom.
-
B.
reformOutcome
Indicates the result or consequence produced by a particular reform or change initiative.
-
C.
councilOutcome
Indicates the result or decision produced by a council after its deliberation or proceedings.
-
D.
outcomeForSingapore
Indicates the resulting impact, consequence, or effect that something has specifically on Singapore.
-
E.
outcomeForEnglish
Indicates the result, consequence, or status specifically associated with something in the context of English (e.g., English language, subject, or setting).
- 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_69eecda2066c8190a344218afa5e89c1 |
completed | April 27, 2026, 2:44 a.m. |
| NER | Named-entity recognition | batch_69f644de4a84819087ddb84757fc4585 |
completed | May 2, 2026, 6:39 p.m. |
| PD | Predicate disambiguation | batch_69f641dc8ff48190ab575d855616580c |
completed | May 2, 2026, 6:26 p.m. |
| PDg | Predicate description generation | batch_69f643e818d481908fc66bc91bd25d77 |
completed | May 2, 2026, 6:35 p.m. |
Created at: April 27, 2026, 3:24 a.m.