Triple
T18919309
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | County of Mortain |
E462803
|
entity |
| Predicate | RobertCountOfMortainRewardedWith |
P88239
|
FINISHED |
| Object | extensive English lands |
—
|
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: extensive English lands | Statement: [County of Mortain, RobertCountOfMortainRewardedWith, extensive English lands]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: RobertCountOfMortainRewardedWith Context triple: [County of Mortain, RobertCountOfMortainRewardedWith, extensive English lands]
-
A.
reignStartAsDukeOfNormandy
Indicates the date or point in time when an individual began their rule holding the title of Duke of Normandy.
-
B.
reignAsDukeOfNormandyTo
Indicates that one entity holds and exercises the title and authority of Duke of Normandy over another entity (typically a territory or domain).
-
C.
dateOfKnighthood
Indicates the specific date on which an individual was formally granted knighthood.
-
D.
lastKnightAppointed
Indicates that a particular knight is the most recently appointed knight in a given context or order.
-
E.
grantedFiefOf
chosen
Indicates that one party has been formally given control or ownership of a fief (landed estate) by another authority.
- 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_69d8dcfdbbb881909964fa5a75bd0b48 |
completed | April 10, 2026, 11:20 a.m. |
| NER | Named-entity recognition | batch_69e5c629527481909dad169f07df0da4 |
completed | April 20, 2026, 6:22 a.m. |
| PD | Predicate disambiguation | batch_69e4a2e9e6488190ba8df92c8058ed88 |
completed | April 19, 2026, 9:39 a.m. |
Created at: April 10, 2026, 11:59 a.m.