Triple
T1435374
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Topkapi Palace |
E30548
|
entity |
| Predicate | servedAsImperialResidenceFrom |
P29281
|
FINISHED |
| Object | 15th century |
—
|
LITERAL 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: 15th century | Statement: [Topkapi Palace, servedAsImperialResidenceFrom, 15th century]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: servedAsImperialResidenceFrom Context triple: [Topkapi Palace, servedAsImperialResidenceFrom, 15th century]
-
A.
servedAsResidenceOf
Indicates that something functioned as the home or dwelling place of a particular person or group.
-
B.
monarchUsedAsResidence
Indicates that a monarch uses or has used a particular place as their residence.
-
C.
usedAsPresidentialPalaceSince
Indicates that something has served in the role of a presidential palace starting from a specified point in time.
-
D.
yearsInUseAsImperialPalace
Indicates the number of years a place served as the official imperial palace.
-
E.
containsRoyalResidence
Indicates that a location includes or encompasses a residence used by royalty.
- F. None of above. chosen
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_69a498fc69ec8190b61722bd4b67c4d2 |
completed | March 1, 2026, 7:52 p.m. |
| NER | Named-entity recognition | batch_69a4c5ff8dbc81909eafcfc9f2260a22 |
completed | March 1, 2026, 11:04 p.m. |
| PD | Predicate disambiguation | batch_69a4c478f65481909ee716791c663491 |
completed | March 1, 2026, 10:58 p.m. |
| PDg | Predicate description generation | batch_69a4c5fd2c5c81909283b7a74aff89b7 |
completed | March 1, 2026, 11:04 p.m. |
Created at: March 1, 2026, 8 p.m.