Triple
T36920677
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Rundown pub |
E913189
|
entity |
| Predicate | hasMaintenanceLevel |
P204252
|
FINISHED |
| Object | poor maintenance |
—
|
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: poor maintenance | Statement: [Rundown pub, hasMaintenanceLevel, poor maintenance]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasMaintenanceLevel Context triple: [Rundown pub, hasMaintenanceLevel, poor maintenance]
-
A.
hasMaintenance
Indicates that an entity is subject to, associated with, or requires a particular maintenance activity or maintenance record.
-
B.
hasMaintenanceType
Indicates the specific category or kind of maintenance associated with an asset, component, or maintenance event.
-
C.
hasMaintenanceBase
Indicates that an entity is supported, serviced, or maintained at a specific base or maintenance facility.
-
D.
hasWorkingLevel
Indicates that one entity possesses or is assigned a specific operational or functional level within a defined system or context.
-
E.
hasMaintained
Indicates that an entity has continued to keep another entity in a particular state, condition, or relationship over a period of time.
- F. None of above. chosen
Provenance (4 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_6a0357f9670081908a7ba1cd46a0b46a |
completed | May 12, 2026, 4:40 p.m. |
| PD | Predicate disambiguation | batch_6a03575e3258819093303248d1569f95 |
completed | May 12, 2026, 4:37 p.m. |
| PDg | Predicate description generation | batch_6a0357f8aa988190bc30088e509e317d |
completed | May 12, 2026, 4:40 p.m. |
Created at: May 3, 2026, 4:13 p.m.