Triple
T36005801
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Viscount of Beaumont |
E1041267
|
entity |
| Predicate | hasModeOfAcquisition |
P25427
|
FINISHED |
| Object | grant by monarch |
—
|
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: grant by monarch | Statement: [Viscount of Beaumont, hasModeOfAcquisition, grant by monarch]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasModeOfAcquisition Context triple: [Viscount of Beaumont, hasModeOfAcquisition, grant by monarch]
-
A.
modeOfAcquisition
chosen
Indicates the method or process by which something is obtained, gained, or acquired.
-
B.
hasAcquisition
Indicates that one entity has acquired ownership or control of another entity, typically through a purchase or merger transaction.
-
C.
hasAcquisitionType
Indicates the specific kind or category of acquisition relationship that exists between one entity acquiring another.
-
D.
usesAcquisitionModel
Indicates that one entity employs or applies a particular acquisition model as the method or framework for obtaining something.
-
E.
acquiredWith
Indicates that one entity was obtained, purchased, or gained together with or by means of another entity.
- 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_69f76e2a02208190aedd1f9025a8b300 |
completed | May 3, 2026, 3:47 p.m. |
| NER | Named-entity recognition | batch_69ff32b88bf48190b45afd1b60cb511c |
completed | May 9, 2026, 1:12 p.m. |
| PD | Predicate disambiguation | batch_69ff3031e18881908927b2ab452de863 |
completed | May 9, 2026, 1:01 p.m. |
Created at: May 3, 2026, 4:07 p.m.