Triple
T24686
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Harry S. Truman National Historic Site |
E491
|
entity |
| Predicate | tourismType |
P1769
|
FINISHED |
| Object | heritage tourism |
—
|
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: heritage tourism | Statement: [Harry S. Truman National Historic Site, tourismType, heritage tourism]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: tourismType Context triple: [Harry S. Truman National Historic Site, tourismType, heritage tourism]
-
A.
isTouristDestination
Indicates that a place is recognized as a location people commonly visit for leisure, sightseeing, or travel.
-
B.
hasCulturalSignificanceFor
Indicates that something holds particular cultural meaning, value, or importance for a specified group or community.
-
C.
transportType
Indicates the mode or means of transportation used in carrying something or someone from one place to another.
-
D.
notableCamp
Indicates that an entity is a camp that is notable or significant in some recognized way (e.g., historically, culturally, or by prominence).
-
E.
coastType
Indicates the specific kind or classification of a coastline associated with a geographic area.
- 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_69a243b4ac2c8190b93c303df797b7b2 |
completed | Feb. 28, 2026, 1:24 a.m. |
| NER | Named-entity recognition | batch_69a246e94ca881908f7a7d2c0b293033 |
completed | Feb. 28, 2026, 1:37 a.m. |
| PD | Predicate disambiguation | batch_69a246560af88190961ea00b35cf9388 |
completed | Feb. 28, 2026, 1:35 a.m. |
| PDg | Predicate description generation | batch_69a246e7fac481909b0c500d4500650e |
completed | Feb. 28, 2026, 1:37 a.m. |
Created at: Feb. 28, 2026, 1:34 a.m.