Triple

T11843392
Position Surface form Disambiguated ID Type / Status
Subject CA Portes de France–Thionville E281709 entity
Predicate includesCommune P15149 FINISHED
Object Fixem
Fixem is a small commune in northeastern France, situated within the Moselle department in the Grand Est region.
 E949222 NE FINISHED

How this triple was built (4 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: Fixem | Statement: [CA Portes de France–Thionville, includesCommune, Fixem]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Fixem
Context triple: [CA Portes de France–Thionville, includesCommune, Fixem]
  • A. Fixin
    Fixin is a Burgundy wine appellation in eastern France known for its robust red wines made primarily from Pinot Noir.
  • B. Fix
    Fix is a surname most notably associated with American character actor Paul Fix, known for his extensive work in Western films and television.
  • C. SFIX
    SFIX is the stock ticker symbol for Stitch Fix, an online personal styling and clothing subscription service.
  • D. Rectify
    Rectify is an American television drama series that follows a man released from death row as he struggles to reintegrate into his small Southern town and confront the unresolved questions surrounding his conviction.
  • E. Fixing it for Freddie
    "Fixing it for Freddie" is a humorous short story by P. G. Wodehouse featuring his iconic valet-butler duo Jeeves and Bertie Wooster.
  • F. None of above. chosen
  • G. Unsure - the case is ambiguous/there is not enough information to decide.
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: Fixem
Triple: [CA Portes de France–Thionville, includesCommune, Fixem]
Generated description
Fixem is a small commune in northeastern France, situated within the Moselle department in the Grand Est region.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Fixem
Target entity description: Fixem is a small commune in northeastern France, situated within the Moselle department in the Grand Est region.
  • A. Fixin
    Fixin is a Burgundy wine appellation in eastern France known for its robust red wines made primarily from Pinot Noir.
  • B. Fix
    Fix is a surname most notably associated with American character actor Paul Fix, known for his extensive work in Western films and television.
  • C. SFIX
    SFIX is the stock ticker symbol for Stitch Fix, an online personal styling and clothing subscription service.
  • D. Rectify
    Rectify is an American television drama series that follows a man released from death row as he struggles to reintegrate into his small Southern town and confront the unresolved questions surrounding his conviction.
  • E. Fixing it for Freddie
    "Fixing it for Freddie" is a humorous short story by P. G. Wodehouse featuring his iconic valet-butler duo Jeeves and Bertie Wooster.
  • F. None of above. chosen

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_69d6ab287ba48190a5178779fd19b9b7 completed April 8, 2026, 7:23 p.m.
NER Named-entity recognition batch_69d8a65a597c8190b09f57463b279afc completed April 10, 2026, 7:27 a.m.
NED1 Entity disambiguation (via context triple) batch_69f1679729c08190a9f6750586f90d8d completed April 29, 2026, 2:06 a.m.
NEDg Description generation batch_69f17005c318819090e54bc64d135477 completed April 29, 2026, 2:42 a.m.
NED2 Entity disambiguation (via description) batch_69f17814de1881908973af026af5d1d1 completed April 29, 2026, 3:16 a.m.
Created at: April 8, 2026, 9:43 p.m.