Triple
T33393451
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Katharine Hepburn as Eula Goodnight |
E855110
|
entity |
| Predicate | filmIsSequelTo |
P170694
|
FINISHED |
| Object | True Grit |
E243806
|
NE 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 Grit | Statement: [Katharine Hepburn as Eula Goodnight, filmIsSequelTo, True Grit]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: filmIsSequelTo Context triple: [Katharine Hepburn as Eula Goodnight, filmIsSequelTo, True Grit]
-
A.
prequelOrSequelTo
Indicates that one work in a narrative series occurs earlier or later in the storyline or release order relative to another work, as its prequel or sequel.
-
B.
isSequelOrFollowupTo
chosen
Indicates that one work continues, extends, or follows the story, events, or content of another earlier work.
-
C.
hasSequelDepiction
Indicates that one depiction of something is followed by another depiction that continues its story or sequence.
-
D.
isPrequelTo
Indicates that one work or event occurs earlier in time and narratively sets up or leads into another work or event.
-
E.
continuesInSequels
Indicates that an element (such as a character, storyline, or theme) persists and appears again in one or more subsequent works in a series.
- F. None of above.
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_69f3496e3f1c8190bcecfa82aa9d17ff |
completed | April 30, 2026, 12:22 p.m. |
| NER | Named-entity recognition | batch_69f6f38159d08190980ad639e08f00f4 |
completed | May 3, 2026, 7:04 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_6a36117d62d08190b6a9e15968ae5145 |
completed | June 20, 2026, 4:05 a.m. |
| PD | Predicate disambiguation | batch_69f6e3d7bee48190b94e0beb48a1d7fa |
completed | May 3, 2026, 5:57 a.m. |
Created at: May 1, 2026, 1:35 a.m.