Triple
T17356676
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Bagan temples |
E421953
|
entity |
| Predicate | peakNumberOfMonuments |
P32446
|
FINISHED |
| Object | over 10000 temples pagodas and monasteries |
—
|
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: over 10000 temples pagodas and monasteries | Statement: [Bagan temples, peakNumberOfMonuments, over 10000 temples pagodas and monasteries]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: peakNumberOfMonuments Context triple: [Bagan temples, peakNumberOfMonuments, over 10000 temples pagodas and monasteries]
-
A.
hasNumberOfMonuments
chosen
Indicates the specific count of monuments associated with or present in a given entity.
-
B.
significantMonument
Indicates that something is a monument of notable historical, cultural, or symbolic importance.
-
C.
monumentGroup
Indicates that one monument belongs to, or is categorized within, a specific group or collection of monuments.
-
D.
otherMonuments
Indicates that there exists a relationship between an entity and additional monuments that are associated with or related to it in some relevant way.
-
E.
hasNumberOfMuseums
Indicates the quantity of museums associated with a given 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_69d889d520008190a26917a95bf1c2ea |
completed | April 10, 2026, 5:25 a.m. |
| NER | Named-entity recognition | batch_69e43a4976788190b00c00f710be6c46 |
completed | April 19, 2026, 2:13 a.m. |
| PD | Predicate disambiguation | batch_69e3b02662d08190a07d0fb5c04b6f33 |
completed | April 18, 2026, 4:24 p.m. |
Created at: April 10, 2026, 5:44 a.m.