Triple
T10669580
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Yonghegong Lama Temple |
E251450
|
entity |
| Predicate | hasNumberOfMainCourtyards |
P11510
|
FINISHED |
| Object | five |
—
|
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: five | Statement: [Yonghegong Lama Temple, hasNumberOfMainCourtyards, five]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasNumberOfMainCourtyards Context triple: [Yonghegong Lama Temple, hasNumberOfMainCourtyards, five]
-
A.
numberOfMainCourtyards
chosen
Indicates the quantity of primary courtyards associated with an entity.
-
B.
hasCourtyard
Indicates that one entity includes, features, or is characterized by the presence of a courtyard.
-
C.
hasCourtyardFeature
Indicates that a courtyard possesses or includes a specific feature or characteristic.
-
D.
hasMainHall
Indicates that an entity possesses or includes a primary or central hall as a significant internal space.
-
E.
hasCourtyardArea
Indicates that an entity includes or is associated with a courtyard and specifies the size or extent of that courtyard space.
- 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_69d6aa5b0d2881909584b20efc5877f0 |
completed | April 8, 2026, 7:19 p.m. |
| NER | Named-entity recognition | batch_69d6f861513881909b44c711371086b7 |
completed | April 9, 2026, 12:52 a.m. |
| PD | Predicate disambiguation | batch_69d6dd8a93208190a573061387e2aebb |
completed | April 8, 2026, 10:58 p.m. |
Created at: April 8, 2026, 9:09 p.m.