Triple
T4450828
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Pablo Escobar |
E97603
|
entity |
| Predicate | givenName |
P17
|
FINISHED |
| Object | Pablo |
E30439
|
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: Pablo | Statement: [Pablo Escobar, givenName, Pablo]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Pablo Context triple: [Pablo Escobar, givenName, Pablo]
-
A.
Pablo
chosen
Pablo is a given name, especially common in Spanish-speaking countries, that corresponds to the English name Paul.
-
B.
Eduardo
Eduardo is a masculine given name commonly used in Spanish and Portuguese-speaking countries, equivalent to the English name Edward.
-
C.
Paco
Paco is a riverside district in Manila, Philippines, known for its historic sites, markets, and dense urban neighborhoods.
-
D.
Sandro
Sandro is a common Italian given name, typically used as a diminutive or short form of Alessandro.
-
E.
Arturo
Arturo is a masculine given name of Spanish and Italian origin, equivalent to Arthur in English.
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide.
Provenance (3 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_69b3454777808190b78aa9047ba1f018 |
completed | March 12, 2026, 10:59 p.m. |
| NER | Named-entity recognition | batch_69b355f2377c8190b0176b4c6776815e |
completed | March 13, 2026, 12:10 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69b6138b6c8c8190a21ad00fb230c0f0 |
completed | March 15, 2026, 2:03 a.m. |
Created at: March 12, 2026, 11:33 p.m.