Triple
T31338338
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Renji Hospital |
E799236
|
entity |
| Predicate | oneOfTheOldestHospitalsIn |
P58759
|
FINISHED |
| Object | Shanghai |
—
|
NE NERFINISHED |
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: Shanghai | Statement: [Renji Hospital, oneOfTheOldestHospitalsIn, Shanghai]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: oneOfTheOldestHospitalsIn Context triple: [Renji Hospital, oneOfTheOldestHospitalsIn, Shanghai]
-
A.
foundedAsHospital
Indicates that an organization was originally established as a hospital.
-
B.
oneOfOldestChurchesIn
Indicates that the subject is among the oldest churches located in the specified place.
-
C.
hospitalEstablishedIn
Indicates that a hospital was founded, opened, or began operating in a specific year or time period.
-
D.
foundedHospitalBy
Indicates that a hospital was established or created by a specific person or organization.
-
E.
oneOfTheOldestOn
chosen
Indicates that one entity is among the earliest or longest-existing examples within the set defined by another entity.
- F. None of above.
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_69f224e3f6ac8190a13488516abca7c9 |
completed | April 29, 2026, 3:33 p.m. |
| NER | Named-entity recognition | batch_69f69f11ba548190b8ad25fafb07b62b |
completed | May 3, 2026, 1:04 a.m. |
| PD | Predicate disambiguation | batch_69f69d1d25e88190a7f57d323574da90 |
completed | May 3, 2026, 12:55 a.m. |
Created at: April 29, 2026, 9:16 p.m.