Triple
T25381564
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Colțea Hospital |
E631400
|
entity |
| Predicate | oneOfOldestHospitalsIn |
P90484
|
FINISHED |
| Object | Bucharest |
E31636
|
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: Bucharest | Statement: [Colțea Hospital, oneOfOldestHospitalsIn, Bucharest]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: oneOfOldestHospitalsIn Context triple: [Colțea Hospital, oneOfOldestHospitalsIn, Bucharest]
-
A.
foundedAsHospital
Indicates that an organization was originally established as a hospital.
-
B.
hospitalEstablishedIn
Indicates that a hospital was founded, opened, or began operating in a specific year or time period.
-
C.
foundedHospitalBy
Indicates that a hospital was established or created by a specific person or organization.
-
D.
oldestInstitutionIn
chosen
Indicates that an institution is the most ancient or earliest-established one within a specified location or group.
-
E.
isOldestMuseumIn
Indicates that a museum is the most ancient or earliest established museum within a specified location or region.
- F. None of above.
Provenance (4 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_69e75a8c50788190aabaa9f96710fc43 |
completed | April 21, 2026, 11:07 a.m. |
| NER | Named-entity recognition | batch_69f55e6016908190957eb98ac70ec280 |
completed | May 2, 2026, 2:16 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_6a10ec80b0048190b128ae6b37a48d65 |
completed | May 22, 2026, 11:53 p.m. |
| PD | Predicate disambiguation | batch_69f4683b34748190818428489a226124 |
completed | May 1, 2026, 8:45 a.m. |
Created at: April 21, 2026, 1:46 p.m.