Triple
T21235995
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Battle of Nesjar |
E523343
|
entity |
| Predicate | OlafHaraldssonRole |
P143314
|
FINISHED |
| Object | claimant to the Norwegian throne |
—
|
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: claimant to the Norwegian throne | Statement: [Battle of Nesjar, OlafHaraldssonRole, claimant to the Norwegian throne]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: OlafHaraldssonRole Context triple: [Battle of Nesjar, OlafHaraldssonRole, claimant to the Norwegian throne]
-
A.
roleInHeorot
Indicates a person's specific function, position, or responsibility within the social or organizational setting of Heorot.
-
B.
heirOf
Indicates that one entity is the legal or designated successor who inherits from another entity, typically upon that entity’s death or transfer of rights.
-
C.
roleInThor
Indicates that an entity has a specific role or character assignment in the context of the work "Thor."
-
D.
GameOfThronesRole
Indicates that one entity plays, voices, or otherwise portrays a character in the television series "Game of Thrones" in relation to another entity.
-
E.
roleInShrekTheThird
Indicates that an entity has a specific role or part in the movie "Shrek the Third."
- 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_69e0b513b89c81908b27147e91368db2 |
completed | April 16, 2026, 10:08 a.m. |
| NER | Named-entity recognition | batch_69e735202c7481909c642ddaafb40671 |
completed | April 21, 2026, 8:28 a.m. |
| PD | Predicate disambiguation | batch_69e5f60e1a888190ba75e2e900270a4e |
completed | April 20, 2026, 9:46 a.m. |
| PDg | Predicate description generation | batch_69e5f993240c8190847c0b08e65726c8 |
completed | April 20, 2026, 10:01 a.m. |
Created at: April 16, 2026, 3:46 p.m.