Triple
T18713491
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Istres |
E457575
|
entity |
| Predicate | regionCode |
P208
|
FINISHED |
| Object |
FR-PAC
FR-PAC is the regional code for Provence-Alpes-Côte d'Azur, an administrative region in southeastern France known for its Mediterranean coastline and the Alps.
|
E1338656
|
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: FR-PAC | Statement: [Istres, regionCode, FR-PAC]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: FR-PAC Context triple: [Istres, regionCode, FR-PAC]
-
A.
FrP
FrP is the commonly used abbreviation for Norway's Progress Party, a right-wing political party known for its liberal economic policies and restrictive immigration stance.
-
B.
FRAS
FRAS is a professional post-nominal title indicating fellowship in the Royal Astronomical Society, typically awarded to individuals who have made significant contributions to astronomy or geophysics.
-
C.
FP
FP is the station code for Fehrbelliner Platz, a public transit station in Berlin, Germany.
-
D.
FP
FP is the station code for Floral Park station on the Long Island Rail Road in New York.
-
E.
PAC
PAC is the stock ticker symbol for Grupo Aeroportuario del Pacífico, a major Mexican airport operator that manages multiple airports in the Pacific region.
- 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: FR-PAC Triple: [Istres, regionCode, FR-PAC]
Generated description
FR-PAC is the regional code for Provence-Alpes-Côte d'Azur, an administrative region in southeastern France known for its Mediterranean coastline and the Alps.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: FR-PAC Target entity description: FR-PAC is the regional code for Provence-Alpes-Côte d'Azur, an administrative region in southeastern France known for its Mediterranean coastline and the Alps.
-
A.
FrP
FrP is the commonly used abbreviation for Norway's Progress Party, a right-wing political party known for its liberal economic policies and restrictive immigration stance.
-
B.
FRAS
FRAS is a professional post-nominal title indicating fellowship in the Royal Astronomical Society, typically awarded to individuals who have made significant contributions to astronomy or geophysics.
-
C.
FP
FP is the station code for Fehrbelliner Platz, a public transit station in Berlin, Germany.
-
D.
FP
FP is the station code for Floral Park station on the Long Island Rail Road in New York.
-
E.
PAC
PAC is the stock ticker symbol for Grupo Aeroportuario del Pacífico, a major Mexican airport operator that manages multiple airports in the Pacific region.
- 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_69d8d392aad081909fe31aa03e6e97d1 |
completed | April 10, 2026, 10:40 a.m. |
| NER | Named-entity recognition | batch_69e56ab352b481909b444e7c476898f4 |
completed | April 19, 2026, 11:52 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_6a052b413d348190b34e236d44fb541a |
completed | May 14, 2026, 1:54 a.m. |
| NEDg | Description generation | batch_6a052c40cd04819096757952a275ddcf |
completed | May 14, 2026, 1:58 a.m. |
| NED2 | Entity disambiguation (via description) | batch_6a052d1122ac819081c664d90d784a82 |
completed | May 14, 2026, 2:01 a.m. |
Created at: April 10, 2026, 11:50 a.m.