Triple
T1053859
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Rue André Pascal |
E22757
|
entity |
| Predicate | hasHouseNumberForOECD |
P22944
|
FINISHED |
| Object | 2 |
—
|
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: 2 | Statement: [Rue André Pascal, hasHouseNumberForOECD, 2]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasHouseNumberForOECD Context triple: [Rue André Pascal, hasHouseNumberForOECD, 2]
-
A.
numberOfHousingUnits
Indicates the total count of distinct housing units associated with an entity or within a specified area.
-
B.
hasNumberOfHouses
Indicates the quantity of houses associated with a given entity.
-
C.
numberOfHouses
Indicates the quantity of houses associated with a given entity or context.
-
D.
boroughNumber
Indicates the numerical identifier assigned to a specific borough within a larger administrative or municipal division.
-
E.
usesHarmonizedNumberingWith
Indicates that two entities apply the same standardized numbering scheme so their identifiers or codes are directly comparable or aligned.
- 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_69a493da02e081908c13ff5e02a0fe7a |
completed | March 1, 2026, 7:30 p.m. |
| NER | Named-entity recognition | batch_69a4b8d669448190955507e2e4975b9f |
completed | March 1, 2026, 10:08 p.m. |
| PD | Predicate disambiguation | batch_69a4b731e25c8190b5ea8466648c2c9a |
completed | March 1, 2026, 10:01 p.m. |
| PDg | Predicate description generation | batch_69a4b7da38888190a118ef20ce4ae9aa |
completed | March 1, 2026, 10:04 p.m. |
Created at: March 1, 2026, 7:42 p.m.