Triple

T37146707
Position Surface form Disambiguated ID Type / Status
Subject Fortress of Salses E920259 entity
Predicate locatedInRegion P40 FINISHED
Object Pyrénées-Orientales
Pyrénées-Orientales is a department in southern France bordering Spain and the Mediterranean Sea, known for its Catalan culture, coastal resorts, and Pyrenean mountain landscapes.
E1204820 NE 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: Pyrénées-Orientales | Statement: [Fortress of Salses, locatedInRegion, Pyrénées-Orientales]
NEDg Description generation gpt-5.1
Instruction
Generate a one-sentence description of the target entity. 
You are given a context triple in the form (subject, predicate, object), where the object is the target entity. 
# Instructions
Use the triple to infer relevant information about the entity. Describe the entity based on what is most defining, well-known. 
Avoid repeating the information from the triple, unless really essential.
# Response Format
Return only the sentence: "Description: [one-sentence description of the target entity]"
Input
Entity: Pyrénées-Orientales
Triple: [Fortress of Salses, locatedInRegion, Pyrénées-Orientales]
Generated description
Pyrénées-Orientales is a department in southern France bordering Spain and the Mediterranean Sea, known for its Catalan culture, coastal resorts, and Pyrenean mountain landscapes.

Provenance (5 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_69f76e9f87c08190b4c8f7fafbd8345a completed May 3, 2026, 3:49 p.m.
NER Named-entity recognition batch_69fb3088d4208190a70c499996213e7b completed May 6, 2026, 12:14 p.m.
NED1 Entity disambiguation (via context triple) batch_6a40360792a48190905ec9a13fb63a20 completed June 27, 2026, 8:43 p.m.
NEDg Description generation batch_6a4036aa606081908c37cae19a44be22 completed June 27, 2026, 8:46 p.m.
NED2 Entity disambiguation (via description) batch_6a4038210f388190a2546f1de996a3db completed June 27, 2026, 8:52 p.m.
Created at: May 3, 2026, 4:15 p.m.