Triple
T38428105
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Parisian Plaine |
E903417
|
entity |
| Predicate | historicalRelationToParis |
P77469
|
FINISHED |
| Object | food supply area for Paris |
—
|
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: food supply area for Paris | Statement: [Parisian Plaine, historicalRelationToParis, food supply area for Paris]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: historicalRelationToParis Context triple: [Parisian Plaine, historicalRelationToParis, food supply area for Paris]
-
A.
relationshipToParis
Indicates the specific type of connection or association an entity has with Paris.
-
B.
historicalCityCorrespondence
Indicates a relationship where one city historically corresponds to, or is considered the historical counterpart or predecessor of, another city.
-
C.
timeInHistoryOfFrance
Indicates a temporal relationship specifying that something occurs during a particular period in the historical timeline of France.
-
D.
associatedWithCityHistory
chosen
Indicates a relationship where something is connected or relevant to the historical events, development, or heritage of a particular city.
-
E.
chronologicalRelationWithinCity
Indicates a temporal ordering between events or entities that occur within the same city.
- 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_69f76e67e4fc8190a7d08dfe9a8af998 |
completed | May 3, 2026, 3:48 p.m. |
| NER | Named-entity recognition | batch_6a0248062e608190aae1afdae38d2e5a |
completed | May 11, 2026, 9:20 p.m. |
| PD | Predicate disambiguation | batch_6a02465a0d38819084c3a6813fb943fc |
completed | May 11, 2026, 9:12 p.m. |
Created at: May 3, 2026, 4:31 p.m.