Triple
T20141127
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Things Heard & Seen |
E491165
|
entity |
| Predicate | hasGhostElements |
P138827
|
FINISHED |
| Object | true |
—
|
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: true | Statement: [Things Heard & Seen, hasGhostElements, true]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasGhostElements Context triple: [Things Heard & Seen, hasGhostElements, true]
-
A.
hasGhostCharacter
Indicates that an entity includes, features, or is associated with a character that is a ghost.
-
B.
hasGhostStations
Indicates that a transportation system or network includes disused, closed, or never-opened stations that still physically exist.
-
C.
hasMainElements
Indicates that something possesses or is composed of its primary or most important constituent parts.
-
D.
hasGhostHouse
Indicates that an entity possesses, contains, or is associated with a house believed to be haunted or inhabited by ghosts.
-
E.
hasSpaceBetweenElements
Indicates that there is a physical or conceptual gap or separation between the referenced elements.
- 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_69da6265f8f0819080b29c752a574088 |
completed | April 11, 2026, 3:01 p.m. |
| NER | Named-entity recognition | batch_69e6679b179c8190a9511df8ed82098a |
completed | April 20, 2026, 5:51 p.m. |
| PD | Predicate disambiguation | batch_69e54cfb0d0081908e789b9b57e96668 |
completed | April 19, 2026, 9:45 p.m. |
| PDg | Predicate description generation | batch_69e54fc2bc3c819088c33cd263303433 |
completed | April 19, 2026, 9:57 p.m. |
Created at: April 11, 2026, 11:32 p.m.