Triple
T1169982
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Recife |
E24891
|
entity |
| Predicate | hasPart |
P35
|
FINISHED |
| Object |
Pau-Ferro
Pau-Ferro is a neighborhood in the city of Recife, Brazil.
|
E139233
|
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: Pau-Ferro | Statement: [Recife, hasPart, Pau-Ferro]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Pau-Ferro Context triple: [Recife, hasPart, Pau-Ferro]
-
A.
Pau
Pau is a historic city in southwestern France, known as the capital of the Pyrénées-Atlantiques department and for its scenic location near the Pyrenees mountains.
-
B.
Marvejols
Marvejols is a historic town in southern France’s Lozère department, known for its medieval heritage and location near the Aubrac and Margeride regions.
-
C.
Céret
Céret is a historic town in southern France near the Spanish border, renowned for its modern art museum and its association with early 20th-century artists like Picasso and Braque.
-
D.
Girona
Girona is a historic city in northeastern Catalonia, Spain, known for its well-preserved medieval architecture, walled Old Quarter, and prominent cathedral.
-
E.
Ayguemarse
Ayguemarse is a smaller watercourse in southeastern France that serves as one of the contributing streams feeding the Ouvèze River.
- 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: Pau-Ferro Triple: [Recife, hasPart, Pau-Ferro]
Generated description
Pau-Ferro is a neighborhood in the city of Recife, Brazil.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Pau-Ferro Target entity description: Pau-Ferro is a neighborhood in the city of Recife, Brazil.
-
A.
Pau
Pau is a historic city in southwestern France, known as the capital of the Pyrénées-Atlantiques department and for its scenic location near the Pyrenees mountains.
-
B.
Marvejols
Marvejols is a historic town in southern France’s Lozère department, known for its medieval heritage and location near the Aubrac and Margeride regions.
-
C.
Céret
Céret is a historic town in southern France near the Spanish border, renowned for its modern art museum and its association with early 20th-century artists like Picasso and Braque.
-
D.
Girona
Girona is a historic city in northeastern Catalonia, Spain, known for its well-preserved medieval architecture, walled Old Quarter, and prominent cathedral.
-
E.
Ayguemarse
Ayguemarse is a smaller watercourse in southeastern France that serves as one of the contributing streams feeding the Ouvèze River.
- 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_69a494082a7c819095004f423f294a64 |
completed | March 1, 2026, 7:31 p.m. |
| NER | Named-entity recognition | batch_69a4bce821b481908bc278a3fa7973f4 |
completed | March 1, 2026, 10:25 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69ac8311ba6481908aaca4c1e9d8b78f |
completed | March 7, 2026, 7:57 p.m. |
| NEDg | Description generation | batch_69ac83add3608190be198ba153721d5c |
completed | March 7, 2026, 7:59 p.m. |
| NED2 | Entity disambiguation (via description) | batch_69ac846e724081909696c8c44f2f9500 |
completed | March 7, 2026, 8:02 p.m. |
Created at: March 1, 2026, 7:45 p.m.