Triple
T24652893
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Plaça de la Constitució |
E610301
|
entity |
| Predicate | hasNameMeaning |
P1966
|
FINISHED |
| Object |
Constitution Square
Constitution Square is a central public plaza, typically found in Spanish-speaking cities, often serving as a historic and civic gathering place associated with constitutional or political events.
|
E1645788
|
NE FINISHED |
How this triple was built (2 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: Constitution Square | Statement: [Plaça de la Constitució, hasNameMeaning, Constitution Square]
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: Constitution Square Triple: [Plaça de la Constitució, hasNameMeaning, Constitution Square]
Generated description
Constitution Square is a central public plaza, typically found in Spanish-speaking cities, often serving as a historic and civic gathering place associated with constitutional or political events.
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_69e2c4d350a481909170482bc2ce6af9 |
completed | April 17, 2026, 11:40 p.m. |
| NER | Named-entity recognition | batch_69f40f87337481909ce868ba29ecdf85 |
completed | May 1, 2026, 2:27 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_6a10049ac3a481909fc8eae6b8f9cdf8 |
completed | May 22, 2026, 7:24 a.m. |
| NEDg | Description generation | batch_6a10095d986881909082cc5a32b6d56e |
completed | May 22, 2026, 7:44 a.m. |
| NED2 | Entity disambiguation (via description) | batch_6a1009d311b08190acf35a3ed552b9c1 |
completed | May 22, 2026, 7:46 a.m. |
Created at: April 18, 2026, 2:34 a.m.