Triple
T2381305
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Pont de l’Alma |
E46316
|
entity |
| Predicate | reconstructionReason |
P6009
|
FINISHED |
| Object | structural problems |
—
|
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: structural problems | Statement: [Pont de l’Alma, reconstructionReason, structural problems]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: reconstructionReason Context triple: [Pont de l’Alma, reconstructionReason, structural problems]
-
A.
reconstructionFor
Indicates that one entity serves as a reconstruction, restoration, or rebuilt version of another entity.
-
B.
reconstructionStatus
Indicates the current state or phase of a reconstruction process that an entity is undergoing or has undergone.
-
C.
statedReason
Indicates that one entity expresses or provides another entity as the explanation, justification, or motive for an action, event, or claim.
-
D.
reasonForChange
chosen
Indicates that one entity serves as the cause, justification, or motivation for a modification or change in another entity or state.
-
E.
reconstructedIn
Indicates that something has been rebuilt, restored, or re-created within a particular context, location, or medium.
- 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_69a88a1554a48190a0180682bcf099be |
completed | March 4, 2026, 7:37 p.m. |
| NER | Named-entity recognition | batch_69abc7b7c9188190a824e4b469bc1548 |
completed | March 7, 2026, 6:37 a.m. |
| PD | Predicate disambiguation | batch_69abc59f73f08190924a36d7d475d8f4 |
completed | March 7, 2026, 6:28 a.m. |
Created at: March 4, 2026, 7:57 p.m.