Triple
T564715
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Place Masséna |
E13527
|
entity |
| Predicate | buildingCountApproximate |
P11484
|
FINISHED |
| Object | several multi-storey blocks with arcades |
—
|
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: several multi-storey blocks with arcades | Statement: [Place Masséna, buildingCountApproximate, several multi-storey blocks with arcades]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: buildingCountApproximate Context triple: [Place Masséna, buildingCountApproximate, several multi-storey blocks with arcades]
-
A.
numberOfBuildings
chosen
Indicates the total count of buildings associated with a given entity or within a specified context.
-
B.
numberBuilt
Indicates the total count of items or structures that have been constructed or produced.
-
C.
numberOfTowers
Indicates the quantity of towers associated with or contained by a given entity.
-
D.
numberOfHouses
Indicates the quantity of houses associated with a given entity or context.
-
E.
buildingType
Indicates the specific category or function that characterizes what kind of building something is.
- 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_69a4933edcf08190b35ecfd6014caee6 |
completed | March 1, 2026, 7:27 p.m. |
| NER | Named-entity recognition | batch_69a49a735b2881908293ad21ad41cdd6 |
completed | March 1, 2026, 7:58 p.m. |
| PD | Predicate disambiguation | batch_69a494c044648190a98589ab18935216 |
completed | March 1, 2026, 7:34 p.m. |
Created at: March 1, 2026, 7:32 p.m.