Triple
T7777962
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Hôtel-Dieu de Paris |
E221441
|
entity |
| Predicate | isOldestHospitalIn |
P58759
|
FINISHED |
| Object | Paris |
E568
|
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: Paris | Statement: [Hôtel-Dieu de Paris, isOldestHospitalIn, Paris]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Paris Context triple: [Hôtel-Dieu de Paris, isOldestHospitalIn, Paris]
-
A.
Paris
Paris is a prince of Troy in Greek mythology, best known for judging the beauty contest of the goddesses and for abducting Helen, which sparked the Trojan War.
-
B.
Paris
chosen
Paris is the capital and largest city of France, renowned for its historic architecture, art, fashion, and cultural influence worldwide.
-
C.
Paris
Paris is a major Chilean department store and retail chain offering a wide range of apparel, home goods, and consumer products.
-
D.
Paris
Paris is a budget-oriented AMD Sempron processor core designed for entry-level desktop computing.
-
E.
Parigi
Parigi is a coastal town that serves as the administrative center of Parigi Moutong Regency in Central Sulawesi, Indonesia.
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide.
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: isOldestHospitalIn Context triple: [Hôtel-Dieu de Paris, isOldestHospitalIn, Paris]
-
A.
isOldestMuseumIn
Indicates that a museum is the most ancient or earliest established museum within a specified location or region.
-
B.
foundedAsHospital
Indicates that an organization was originally established as a hospital.
-
C.
isOldestCityIn
Indicates that one city holds the distinction of being the most ancient or earliest established within a specified region, country, or group of cities.
-
D.
isOldestCollegeLibraryOf
Indicates that one entity is the oldest existing college library associated with the other entity.
-
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 (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_69ca83ebbef881909ac47f789145fef7 |
completed | March 30, 2026, 2:08 p.m. |
| NER | Named-entity recognition | batch_69cae7e779ec8190b77296d9c2ac3210 |
completed | March 30, 2026, 9:15 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69caf59dfe5c8190972eb9db1b3ca043 |
completed | March 30, 2026, 10:13 p.m. |
| PD | Predicate disambiguation | batch_69caa488532c819093ac40bba0b3c7ef |
completed | March 30, 2026, 4:27 p.m. |
Created at: March 30, 2026, 4:16 p.m.