Triple
T16972924
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Madrid metropolitan area |
E411731
|
entity |
| Predicate | hasMajorBusinessDistrict |
P459
|
FINISHED |
| Object |
AZCA
AZCA is Madrid’s main financial and business district, known for its cluster of skyscrapers, corporate headquarters, and commercial centers.
|
E1242621
|
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: AZCA | Statement: [Madrid metropolitan area, hasMajorBusinessDistrict, AZCA]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: AZCA Context triple: [Madrid metropolitan area, hasMajorBusinessDistrict, AZCA]
-
A.
AZI
AZI is the IATA airport code for Al Bateen Executive Airport in Abu Dhabi, United Arab Emirates.
-
B.
Eza’r
Eza’r is the endonym used by the Chichimeca Jonaz people for their own indigenous community and language in Mexico.
-
C.
ZAZ
ZAZ is the IATA airport code for Zaragoza Airport, a major civilian and military airfield serving the city of Zaragoza in northeastern Spain.
-
D.
Azna
Azna is a small city in western Iran known for its location in the mountainous Lorestan region and its role as a local administrative and commercial center.
-
E.
Azsuna
Azsuna is a broken, magic-scarred coastal zone on the Broken Isles in World of Warcraft, known for its ancient elven ruins, spectral inhabitants, and central role in the Legion expansion’s storyline.
- 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: AZCA Triple: [Madrid metropolitan area, hasMajorBusinessDistrict, AZCA]
Generated description
AZCA is Madrid’s main financial and business district, known for its cluster of skyscrapers, corporate headquarters, and commercial centers.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: AZCA Target entity description: AZCA is Madrid’s main financial and business district, known for its cluster of skyscrapers, corporate headquarters, and commercial centers.
-
A.
AZI
AZI is the IATA airport code for Al Bateen Executive Airport in Abu Dhabi, United Arab Emirates.
-
B.
Eza’r
Eza’r is the endonym used by the Chichimeca Jonaz people for their own indigenous community and language in Mexico.
-
C.
ZAZ
ZAZ is the IATA airport code for Zaragoza Airport, a major civilian and military airfield serving the city of Zaragoza in northeastern Spain.
-
D.
Azna
Azna is a small city in western Iran known for its location in the mountainous Lorestan region and its role as a local administrative and commercial center.
-
E.
Azsuna
Azsuna is a broken, magic-scarred coastal zone on the Broken Isles in World of Warcraft, known for its ancient elven ruins, spectral inhabitants, and central role in the Legion expansion’s storyline.
- 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_69d886ca8f348190812768ea8d5055ce |
completed | April 10, 2026, 5:12 a.m. |
| NER | Named-entity recognition | batch_69e3d0ae47f08190a13e98d20aba7f16 |
completed | April 18, 2026, 6:42 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_6a00d4738fbc819099e8281ebc777091 |
completed | May 10, 2026, 6:54 p.m. |
| NEDg | Description generation | batch_6a00d51835c48190b1a37de6ac25ceaa |
completed | May 10, 2026, 6:57 p.m. |
| NED2 | Entity disambiguation (via description) | batch_6a00d59b96108190a0e55f01529a0b64 |
completed | May 10, 2026, 6:59 p.m. |
Created at: April 10, 2026, 5:31 a.m.