Triple
T1815155
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Pont Alexandre III |
E40419
|
entity |
| Predicate | hasPylon |
P32602
|
FINISHED |
| Object | four 17-metre-high pylons |
—
|
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: four 17-metre-high pylons | Statement: [Pont Alexandre III, hasPylon, four 17-metre-high pylons]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasPylon Context triple: [Pont Alexandre III, hasPylon, four 17-metre-high pylons]
-
A.
hasPilotis
Indicates that a building or structure is elevated on pilotis (supporting columns or stilts), rather than resting directly on the ground.
-
B.
hasPyramid
Indicates that one entity possesses, contains, or features a pyramid in relation to another entity.
-
C.
hasPier
Indicates that a location or structure possesses or includes a pier as part of its features.
-
D.
pylonType
Indicates the specific structural or functional category that a pylon belongs to within a given context.
-
E.
hasTower
Indicates that one entity possesses, contains, or is characterized by the presence of a tower.
- 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_69a8864526c081908a3a4d74f689e2c5 |
completed | March 4, 2026, 7:21 p.m. |
| NER | Named-entity recognition | batch_69aba67721788190951beae25e885457 |
completed | March 7, 2026, 4:15 a.m. |
| PD | Predicate disambiguation | batch_69aa61d884548190a19cf3a6b5ae9d48 |
completed | March 6, 2026, 5:10 a.m. |
| PDg | Predicate description generation | batch_69aba67554788190b429f2b9f0a70310 |
completed | March 7, 2026, 4:15 a.m. |
Created at: March 4, 2026, 7:32 p.m.