Triple
T24007651
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Calle de Atocha |
E594433
|
entity |
| Predicate | hasCulturalSiteAlong |
P28782
|
FINISHED |
| Object |
Teatro Calderón
Teatro Calderón is a historic Madrid theater renowned for its grand architecture and prominent role in the city’s performing arts scene.
|
E1623975
|
NE FINISHED |
How this triple was built (3 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: Teatro Calderón | Statement: [Calle de Atocha, hasCulturalSiteAlong, Teatro Calderón]
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: Teatro Calderón Triple: [Calle de Atocha, hasCulturalSiteAlong, Teatro Calderón]
Generated description
Teatro Calderón is a historic Madrid theater renowned for its grand architecture and prominent role in the city’s performing arts scene.
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasCulturalSiteAlong Context triple: [Calle de Atocha, hasCulturalSiteAlong, Teatro Calderón]
-
A.
hasCulturalHeritageOn
Indicates that one entity possesses, preserves, or is associated with the cultural heritage embodied in another entity.
-
B.
culturalSite
chosen
Indicates that one entity is recognized or designated as a cultural site associated with or located in relation to another entity.
-
C.
hasCulturalSiteType
Indicates that an entity is associated with, or classified by, a specific type or category of cultural site.
-
D.
hasArchaeologicalSitesFrom
Indicates that an entity contains or is associated with archaeological sites dating from a specified time period or era.
-
E.
hasTraditionalCulturalSites
Indicates that an entity possesses or is associated with locations recognized for their traditional or culturally significant heritage.
- F. None of above.
Provenance (6 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_69e288bc8f608190ac4af29f0bd1c744 |
completed | April 17, 2026, 7:23 p.m. |
| NER | Named-entity recognition | batch_69f1d46ba1f88190a204d8cfb0f64be6 |
completed | April 29, 2026, 9:50 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_6a0fbcf591e08190a97da09a9df6f205 |
completed | May 22, 2026, 2:18 a.m. |
| NEDg | Description generation | batch_6a0fbdf3fc5c8190b8dc7e5c2416b02b |
completed | May 22, 2026, 2:22 a.m. |
| NED2 | Entity disambiguation (via description) | batch_6a0fbe7e12188190803c1954112de4e6 |
completed | May 22, 2026, 2:25 a.m. |
| PD | Predicate disambiguation | batch_69f17639d23c8190bed93434e2f9230a |
completed | April 29, 2026, 3:08 a.m. |
Created at: April 17, 2026, 9:40 p.m.