Triple
T14623140
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Seventeen Days |
E343273
|
entity |
| Predicate | guestOnTrack |
P45889
|
FINISHED |
| Object | Bob Seger on "Landing in London" |
—
|
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: Bob Seger on "Landing in London" | Statement: [Seventeen Days, guestOnTrack, Bob Seger on "Landing in London"]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: guestOnTrack Context triple: [Seventeen Days, guestOnTrack, Bob Seger on "Landing in London"]
-
A.
guestConductorOf
Indicates a temporary conducting role where one person serves as the visiting or special conductor for an ensemble, performance, or musical organization.
-
B.
guestStar
chosen
Indicates that one entity appears in a limited, special, or featured role within another entity’s production, event, or context, without being a regular or primary participant.
-
C.
typicalGuests
Indicates the usual or most common guests associated with a particular host, place, or event.
-
D.
guestHosted
Indicates that one entity temporarily hosted or presented an event, show, or program in place of or alongside the usual host.
-
E.
trackOn
Indicates that one entity is physically positioned or moving along the surface or path of another, like a vehicle on a track or rails.
- 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_69d822dffc3c8190aa173b90761bffda |
completed | April 9, 2026, 10:06 p.m. |
| NER | Named-entity recognition | batch_69deb468acc4819083b7e818d5cec809 |
completed | April 14, 2026, 9:40 p.m. |
| PD | Predicate disambiguation | batch_69de656f9f4c81909f815b6629a9ee39 |
completed | April 14, 2026, 4:03 p.m. |
Created at: April 10, 2026, 1:26 a.m.