Triple
T957968
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | The Motherland Calls |
E20665
|
entity |
| Predicate | heightIncludingSword |
P21845
|
FINISHED |
| Object | approximately 85 metres |
—
|
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: approximately 85 metres | Statement: [The Motherland Calls, heightIncludingSword, approximately 85 metres]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: heightIncludingSword Context triple: [The Motherland Calls, heightIncludingSword, approximately 85 metres]
-
A.
heightWithPedestal
Indicates the total vertical measurement of an object including the height of its supporting pedestal.
-
B.
heightInInches
Indicates that one entity has a specific height measured in inches.
-
C.
heightInCentimetres
Indicates the numerical value of an entity’s height measured in centimetres.
-
D.
hasTypicalArmor
Indicates that an entity normally wears or is equipped with a standard or characteristic type of armor.
-
E.
estimatedHeightAtHipsInMeters
Indicates the estimated vertical height, measured in meters, of an entity at the level of its hips.
- 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_69a493b21f2881908132dcf45dcd2f36 |
completed | March 1, 2026, 7:29 p.m. |
| NER | Named-entity recognition | batch_69a4b3fac2bc8190a66feb70c68899b2 |
completed | March 1, 2026, 9:47 p.m. |
| PD | Predicate disambiguation | batch_69a4b2a18ecc8190883f6206fe3b0fb6 |
completed | March 1, 2026, 9:41 p.m. |
| PDg | Predicate description generation | batch_69a4b326d9d88190913c1a892a795707 |
completed | March 1, 2026, 9:44 p.m. |
Created at: March 1, 2026, 7:40 p.m.