Triple
T71332
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Hollywood Sign |
E1427
|
entity |
| Predicate | heightPerLetter |
P3566
|
FINISHED |
| Object | approximately 45 feet |
—
|
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 45 feet | Statement: [Hollywood Sign, heightPerLetter, approximately 45 feet]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: heightPerLetter Context triple: [Hollywood Sign, heightPerLetter, approximately 45 feet]
-
A.
hasStandardLetterCount
Indicates that an entity’s associated text or label contains a number of letters that matches a predefined standard or expected count.
-
B.
typicalHeight
Indicates the usual or characteristic height associated with an entity, such as a person, object, or species.
-
C.
length
Indicates a measurement relationship where a value specifies how long something is from one end to the other.
-
D.
heightWithPedestal
Indicates the total vertical measurement of an object including the height of its supporting pedestal.
-
E.
roofHeight
Indicates the vertical distance or elevation of a roof relative to a reference level or structure.
- 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_69a24c06b3bc8190aa4ac89026115efc |
completed | Feb. 28, 2026, 1:59 a.m. |
| NER | Named-entity recognition | batch_69a24f6997c081908b202f937eb2b14f |
completed | Feb. 28, 2026, 2:14 a.m. |
| PD | Predicate disambiguation | batch_69a24eab7f408190a8275cb82474f575 |
completed | Feb. 28, 2026, 2:10 a.m. |
| PDg | Predicate description generation | batch_69a24f65170c8190bc541c8351456a4d |
completed | Feb. 28, 2026, 2:13 a.m. |
Created at: Feb. 28, 2026, 2:03 a.m.