Triple
T1906135
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Hank Morgan |
E38008
|
entity |
| Predicate | transportMechanism |
P3705
|
FINISHED |
| Object | time travel |
—
|
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: time travel | Statement: [Hank Morgan, transportMechanism, time travel]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: transportMechanism Context triple: [Hank Morgan, transportMechanism, time travel]
-
A.
transitionMechanismUsedWith
chosen
Indicates that a particular transition or change from one state to another is carried out using a specified mechanism or method.
-
B.
transportProtocol
Indicates the communication protocol used to transport data between entities in a networked interaction.
-
C.
transports
Indicates that one entity carries or conveys another entity from one place to another.
-
D.
transportFor
Indicates a relationship where one entity serves as the means or service used to move another entity from one place to another.
-
E.
transportHubType
Indicates the specific category or kind of transport hub associated with an entity (e.g., airport, train station, bus terminal).
- F. None of above.
Provenance (3 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_69a8862a26088190aae5243695aeefc0 |
completed | March 4, 2026, 7:21 p.m. |
| NER | Named-entity recognition | batch_69abb34d94fc8190a5bf1e582c77c725 |
completed | March 7, 2026, 5:10 a.m. |
| PD | Predicate disambiguation | batch_69abafe9f8b0819086d8f6288511c66d |
completed | March 7, 2026, 4:56 a.m. |
Created at: March 4, 2026, 7:35 p.m.