Triple
T5492408
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Roger Mortimer, 1st Earl of March |
E123730
|
entity |
| Predicate | arrestedInYear |
P3170
|
FINISHED |
| Object | 1330 |
—
|
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: 1330 | Statement: [Roger Mortimer, 1st Earl of March, arrestedInYear, 1330]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: arrestedInYear Context triple: [Roger Mortimer, 1st Earl of March, arrestedInYear, 1330]
-
A.
arrestedFor
Indicates that an authority has taken someone into custody because they are suspected or accused of committing a specified offense or wrongdoing.
-
B.
arrestedAt
Indicates that an entity was apprehended or taken into custody at a specific location or during a specific event or time.
-
C.
dateOfArrest
chosen
Indicates the specific date on which an entity was formally arrested by an authority.
-
D.
convictionYear
Indicates the calendar year in which an entity was formally convicted of an offense.
-
E.
imprisonmentYear
Indicates the specific year in which an entity was imprisoned or placed into custody.
- 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_69bd464a2d908190869324ce176779c8 |
completed | March 20, 2026, 1:06 p.m. |
| NER | Named-entity recognition | batch_69bd9280403c8190baaa3f7923449a37 |
completed | March 20, 2026, 6:31 p.m. |
| PD | Predicate disambiguation | batch_69bd91a8df6481908d1643f7342fe6f0 |
completed | March 20, 2026, 6:27 p.m. |
Created at: March 20, 2026, 2:10 p.m.