Triple
T680353
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Marco Polo Bridge |
E13167
|
entity |
| Predicate | hasApproximateNumberOfStoneLions |
P6210
|
FINISHED |
| Object | over 200 |
—
|
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 200 | Statement: [Marco Polo Bridge, hasApproximateNumberOfStoneLions, over 200]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasApproximateNumberOfStoneLions Context triple: [Marco Polo Bridge, hasApproximateNumberOfStoneLions, over 200]
-
A.
lionArmedAndLangued
Indicates that a lion is depicted with its claws and tongue emphasized, typically by being shown and colored distinctly.
-
B.
numberOfAnimals
chosen
Indicates the quantity of animals associated with a given entity or context.
-
C.
lionSupporterRepresents
Indicates that an entity serves as a representative or advocate for a lion supporter, acting on their behalf or symbolizing their interests.
-
D.
approximateNumberOfMoai
Indicates that one entity specifies an estimated or approximate count of Moai associated with another entity.
-
E.
hasCrownCount
Indicates the number of crowns that an entity possesses or is associated with.
- 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_69a4933d3bf88190972041cd8cf143b9 |
completed | March 1, 2026, 7:27 p.m. |
| NER | Named-entity recognition | batch_69a4a04f4efc819082767a7517fa760a |
completed | March 1, 2026, 8:23 p.m. |
| PD | Predicate disambiguation | batch_69a49d1d79608190a849ba9ffad2879d |
completed | March 1, 2026, 8:10 p.m. |
Created at: March 1, 2026, 7:36 p.m.