Triple
T1667491
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Social Statics |
E36045
|
entity |
| Predicate | positionOnLand |
P8266
|
FINISHED |
| Object | questions absolute private ownership of land |
—
|
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: questions absolute private ownership of land | Statement: [Social Statics, positionOnLand, questions absolute private ownership of land]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: positionOnLand Context triple: [Social Statics, positionOnLand, questions absolute private ownership of land]
-
A.
usesOnLand
Indicates that one entity employs or operates another entity specifically in a land-based context.
-
B.
positionOn
Indicates that one entity is located on top of or at a specific place along the surface or extent of another entity.
-
C.
landedNear
Indicates that one entity has come to rest on a surface or location in close proximity to another specified entity or reference point.
-
D.
positionRelativeToCoast
Indicates the spatial relationship of something to a coastline, such as its distance or orientation relative to the coast.
-
E.
hasPositionOn
chosen
Indicates that one entity occupies or holds a specific role, job, or spatial location relative to 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_69a8861286808190939afff3ce8ee31e |
completed | March 4, 2026, 7:20 p.m. |
| NER | Named-entity recognition | batch_69abc0e8d5648190915ff689c7ca42bc |
completed | March 7, 2026, 6:08 a.m. |
| PD | Predicate disambiguation | batch_69a907d331748190963d4ab1a2741537 |
completed | March 5, 2026, 4:34 a.m. |
Created at: March 4, 2026, 7:29 p.m.