Triple
T20664589
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | The Land Before Time |
E507850
|
entity |
| Predicate | numberOfDirectToVideoSequels |
P140974
|
FINISHED |
| Object | 13 |
—
|
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: 13 | Statement: [The Land Before Time, numberOfDirectToVideoSequels, 13]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: numberOfDirectToVideoSequels Context triple: [The Land Before Time, numberOfDirectToVideoSequels, 13]
-
A.
hasSequelDepiction
Indicates that one depiction of something is followed by another depiction that continues its story or sequence.
-
B.
hasSequelAdaptation
Indicates that an original work has a subsequent adaptation that continues its story or follows it in sequence.
-
C.
hasSequelOrRelated
Indicates that one work follows, continues, or is otherwise narratively or thematically related to another work.
-
D.
hasUnofficialSequels
Indicates that a work is followed by one or more subsequent works that continue its story or concept without being officially recognized as canonical sequels.
-
E.
hasSequelShotBackToBackWith
Indicates that two sequels were filmed consecutively or simultaneously as part of the same production schedule.
- 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_69e0b4c059bc81908ea762cd73ea4424 |
completed | April 16, 2026, 10:06 a.m. |
| NER | Named-entity recognition | batch_69e6b2f541bc8190ac7946b91647f2b0 |
completed | April 20, 2026, 11:12 p.m. |
| PD | Predicate disambiguation | batch_69e5c0315f5081908098707c6455e56e |
completed | April 20, 2026, 5:57 a.m. |
| PDg | Predicate description generation | batch_69e5c3caef50819093c8159fe8d6435b |
completed | April 20, 2026, 6:12 a.m. |
Created at: April 16, 2026, 11:44 a.m.