Triple
T13831785
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | One Day as a Lion |
E332414
|
entity |
| Predicate | hasEPTrackCount |
P1707
|
FINISHED |
| Object | 5 |
—
|
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: 5 | Statement: [One Day as a Lion, hasEPTrackCount, 5]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasEPTrackCount Context triple: [One Day as a Lion, hasEPTrackCount, 5]
-
A.
numberOfTracks
chosen
Indicates the quantity of tracks associated with a given entity.
-
B.
hasEP
Indicates that an entity possesses, is associated with, or is characterized by a specific EP (e.g., an endpoint, event point, or designated EP resource) in the given context.
-
C.
hasTrack
Indicates that one entity possesses, includes, or is associated with a specific track (such as a path, course, or recorded item).
-
D.
hasTwoTracks
Indicates that the subject possesses or is associated with exactly two distinct tracks or pathways.
-
E.
containsAdditionalTracksBeyond
Indicates that one entity includes more tracks or items than are present in another referenced set or version.
- 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_69d81c5ae7c88190b0dd41bdafeb5999 |
completed | April 9, 2026, 9:38 p.m. |
| NER | Named-entity recognition | batch_69de0299334481908c2b271eaf06e4b7 |
completed | April 14, 2026, 9:02 a.m. |
| PD | Predicate disambiguation | batch_69dbc86668e08190ba9135d1c3f38d35 |
completed | April 12, 2026, 4:29 p.m. |
Created at: April 9, 2026, 10:13 p.m.