Triple
T15932914
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Giant Lantern Festival |
E386365
|
entity |
| Predicate | typicalLanternDiameter |
P121042
|
FINISHED |
| Object | up to several meters |
—
|
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: up to several meters | Statement: [Giant Lantern Festival, typicalLanternDiameter, up to several meters]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: typicalLanternDiameter Context triple: [Giant Lantern Festival, typicalLanternDiameter, up to several meters]
-
A.
lanternColor
Indicates that one entity specifies or describes the color attribute of a lantern associated with another entity.
-
B.
hasDomeLantern
Indicates that one entity possesses or features a dome-shaped lantern structure as part of its form or design.
-
C.
hasLanternShape
Indicates that one entity has the form, outline, or configuration characteristic of a lantern.
-
D.
hasLanternLightSource
Indicates that an entity uses a lantern as its source of light.
-
E.
shellDiameter
Indicates the diameter measurement of a shell, typically specifying the distance across it at its widest point.
- 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_69d86da750008190987eb26be3f6c118 |
completed | April 10, 2026, 3:25 a.m. |
| NER | Named-entity recognition | batch_69e17d4d08f481909f38b75e3f42d9ab |
completed | April 17, 2026, 12:22 a.m. |
| PD | Predicate disambiguation | batch_69e142d37cd88190ab50760f1783e20c |
completed | April 16, 2026, 8:13 p.m. |
| PDg | Predicate description generation | batch_69e17d48cc9c8190b03fd07ae2e9dfd8 |
completed | April 17, 2026, 12:22 a.m. |
Created at: April 10, 2026, 4:53 a.m.