Triple

T36099693
Position Surface form Disambiguated ID Type / Status
Subject Golfe de Fos E1044166 entity
Predicate hasPort P35 FINISHED
Object Port of Fos-sur-Mer
The Port of Fos-sur-Mer is a major deep-water industrial and commercial seaport in southern France that forms the western part of the Port of Marseille-Fos complex on the Mediterranean coast.
E2168438 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: Port of Fos-sur-Mer | Statement: [Golfe de Fos, hasPort, Port of Fos-sur-Mer]
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: Port of Fos-sur-Mer
Triple: [Golfe de Fos, hasPort, Port of Fos-sur-Mer]
Generated description
The Port of Fos-sur-Mer is a major deep-water industrial and commercial seaport in southern France that forms the western part of the Port of Marseille-Fos complex on the Mediterranean coast.

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_69f76e338e2c8190b7f3bc68bec76349 completed May 3, 2026, 3:48 p.m.
NER Named-entity recognition batch_69f7b28eb9f48190af70ef74de96e306 completed May 3, 2026, 8:39 p.m.
NED1 Entity disambiguation (via context triple) batch_6a38d54c827081909ec1924509525351 completed June 22, 2026, 6:25 a.m.
NEDg Description generation batch_6a38d5e83b58819080bd6a95a17f6b2b completed June 22, 2026, 6:27 a.m.
NED2 Entity disambiguation (via description) batch_6a38d681cf388190896a30e2b0939181 completed June 22, 2026, 6:30 a.m.
Created at: May 3, 2026, 4:08 p.m.