Triple
T36920686
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Rundown pub |
E913189
|
entity |
| Predicate | hasFurnitureCondition |
P151983
|
FINISHED |
| Object | worn furniture |
—
|
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: worn furniture | Statement: [Rundown pub, hasFurnitureCondition, worn furniture]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasFurnitureCondition Context triple: [Rundown pub, hasFurnitureCondition, worn furniture]
-
A.
containsFurnitureBy
Indicates that one entity includes or holds furniture items that are provided, created, or specified by another entity.
-
B.
interiorCondition
chosen
Indicates the state or quality of the inside of an object, space, or structure, such as its cleanliness, damage, or overall upkeep.
-
C.
conditionOfGoods
Indicates the state, quality, or integrity that the goods are in at a given time or upon a specified event.
-
D.
bowSectionCondition
Indicates the condition or state of the bow section of an object, typically assessing its integrity, damage, or maintenance status.
-
E.
furnishingType
Indicates the type or category of furnishings associated with an entity, such as a property or room.
- 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_69f76e885b848190bad82c87e9525486 |
completed | May 3, 2026, 3:49 p.m. |
| NER | Named-entity recognition | batch_69fb563aec448190875410fb1a3ed624 |
completed | May 6, 2026, 2:54 p.m. |
| PD | Predicate disambiguation | batch_69fb35b9ede881908aaae93a215525df |
completed | May 6, 2026, 12:36 p.m. |
Created at: May 3, 2026, 4:13 p.m.