Triple
T27254947
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Lord of Montfort |
E687586
|
entity |
| Predicate | hasSocioeconomicRole |
P89201
|
FINISHED |
| Object | landholding aristocracy |
—
|
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: landholding aristocracy | Statement: [Lord of Montfort, hasSocioeconomicRole, landholding aristocracy]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasSocioeconomicRole Context triple: [Lord of Montfort, hasSocioeconomicRole, landholding aristocracy]
-
A.
socioeconomicRole
chosen
Indicates the social and economic position, function, or status an entity holds within a society or system.
-
B.
hasEconomicRole
Indicates that an entity participates in or fulfills a specific function, position, or responsibility within an economic system or activity.
-
C.
hasSocioEconomicContext
Indicates the broader social and economic conditions or circumstances within which an entity, event, or relationship occurs or is interpreted.
-
D.
hasSocioeconomicIssue
Indicates that an entity is affected by, associated with, or involved in a socioeconomic problem or challenge.
-
E.
hasOnScreenSocioeconomicStatus
Indicates that an entity is depicted or characterized with a particular socioeconomic status within an on-screen or audiovisual context.
- 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_69ef35567e808190a94458cd44ebff0c |
completed | April 27, 2026, 10:07 a.m. |
| NER | Named-entity recognition | batch_69f68f670b608190a0b6ab60d722b4e0 |
completed | May 2, 2026, 11:57 p.m. |
| PD | Predicate disambiguation | batch_69f68b78f29481908cc8f390496dee97 |
completed | May 2, 2026, 11:40 p.m. |
Created at: April 27, 2026, 10:48 a.m.