Triple
T3637833
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Chiang Kai-shek Memorial Hall |
E77113
|
entity |
| Predicate | numberOfStepsSymbolism |
P49746
|
FINISHED |
| Object | represents Chiang Kai-shek's age at death |
—
|
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: represents Chiang Kai-shek's age at death | Statement: [Chiang Kai-shek Memorial Hall, numberOfStepsSymbolism, represents Chiang Kai-shek's age at death]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: numberOfStepsSymbolism Context triple: [Chiang Kai-shek Memorial Hall, numberOfStepsSymbolism, represents Chiang Kai-shek's age at death]
-
A.
numberOfStepsPerPattern
Indicates the total count of discrete steps involved in a single instance of the pattern.
-
B.
numberOfStepsToSummit
Indicates the total count of steps required to reach the summit from a specified starting point.
-
C.
numberOfStairs
Indicates the quantity of stairs associated with or present in a given context or structure.
-
D.
numberOfStaircases
Indicates the quantity of distinct staircases associated with or present in a given entity or location.
-
E.
digitSymbolForTwo
Indicates the written or printed symbol that represents the numerical value two.
- 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_69ad85dd0be48190b738990cb20c4731 |
completed | March 8, 2026, 2:21 p.m. |
| NER | Named-entity recognition | batch_69adc328e5e481909d26318c743bc84a |
completed | March 8, 2026, 6:42 p.m. |
| PD | Predicate disambiguation | batch_69adb842be7c8190b7dfdb7c906f294c |
completed | March 8, 2026, 5:56 p.m. |
| PDg | Predicate description generation | batch_69adb902e61c81908f10494f828e260f |
completed | March 8, 2026, 5:59 p.m. |
Created at: March 8, 2026, 3:24 p.m.