Triple
T31222883
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Le Clémentin de Pape Clément (red) |
E796061
|
entity |
| Predicate | estateNearbyCity |
P171038
|
FINISHED |
| Object | Bordeaux |
—
|
NE NERFINISHED |
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: Bordeaux | Statement: [Le Clémentin de Pape Clément (red), estateNearbyCity, Bordeaux]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: estateNearbyCity Context triple: [Le Clémentin de Pape Clément (red), estateNearbyCity, Bordeaux]
-
A.
nearbyEstate
Indicates that one estate is located close to another estate in physical space.
-
B.
realEstate
Indicates a relationship where an entity owns, manages, or is otherwise associated with real property such as land or buildings.
-
C.
propertyMarket
Indicates a relationship where real estate or properties are being offered, traded, or evaluated within a market context.
-
D.
realEstateDemand
Indicates the level or presence of interest and desire among potential buyers or renters for a particular piece of real estate.
-
E.
realEstateMarketCharacteristic
Indicates a characteristic, condition, or defining feature of a real estate market.
- 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_69f224da98f88190ab32f690cce5d303 |
completed | April 29, 2026, 3:33 p.m. |
| NER | Named-entity recognition | batch_69f69c4f35148190b58e80e79215092d |
completed | May 3, 2026, 12:52 a.m. |
| PD | Predicate disambiguation | batch_69f696673214819094350e1d2648ef34 |
completed | May 3, 2026, 12:27 a.m. |
| PDg | Predicate description generation | batch_69f6978ec27c8190a488e1f9c2566d38 |
completed | May 3, 2026, 12:32 a.m. |
Created at: April 29, 2026, 9:10 p.m.