Triple
T7990821
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Melissa McBride |
E185999
|
entity |
| Predicate | hasScreenPresenceType |
P31835
|
FINISHED |
| Object | series regular (The Walking Dead) |
—
|
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: series regular (The Walking Dead) | Statement: [Melissa McBride, hasScreenPresenceType, series regular (The Walking Dead)]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasScreenPresenceType Context triple: [Melissa McBride, hasScreenPresenceType, series regular (The Walking Dead)]
-
A.
hasScreen
Indicates that an entity is equipped with or includes a screen or display component.
-
B.
hasCharacterPresence
Indicates that a particular character appears or is present within a specified context, such as a scene, work, or medium.
-
C.
hasHumanPresence
Indicates that humans are physically present in or occupying a given location, object, or context.
-
D.
hasNumberOfScreens
Indicates the quantity of screens associated with or contained in a given entity.
-
E.
typeOfPresence
chosen
Indicates the manner or mode in which an entity is present or exists in relation to another entity, context, or environment.
- 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_69ca829c6c308190ab05b43d234c52b2 |
completed | March 30, 2026, 2:03 p.m. |
| NER | Named-entity recognition | batch_69cb3c6fc19c8190b98023e257c2f4f2 |
completed | March 31, 2026, 3:15 a.m. |
| PD | Predicate disambiguation | batch_69cb0483d3b48190b250c7603d747bca |
completed | March 30, 2026, 11:17 p.m. |
Created at: March 30, 2026, 5:16 p.m.