Triple
T30208235
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Green Lady ghost |
E767996
|
entity |
| Predicate | colorOfApparition |
P177573
|
FINISHED |
| Object | green |
—
|
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: green | Statement: [Green Lady ghost, colorOfApparition, green]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: colorOfApparition Context triple: [Green Lady ghost, colorOfApparition, green]
-
A.
associatedWithApparition
Indicates a relationship where something is linked or connected to an apparition, such as being caused by, accompanying, or characterizing that apparition.
-
B.
colorAtUnveiling
Indicates the color an object or item had at the specific moment it was first revealed or unveiled.
-
C.
apparitionLittéraire
Indicates the event or relationship of a literary work or text coming into public existence, such as its first publication or debut in the literary sphere.
-
D.
apparitionFrequency
Indicates how often an entity appears, manifests, or becomes perceptible within a given context or timeframe.
-
E.
capeColor
Indicates the color attribute associated with a cape worn or possessed by an entity.
- 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_69f2247eb0848190b4032f302d39c0d9 |
completed | April 29, 2026, 3:32 p.m. |
| NER | Named-entity recognition | batch_69f7009d39508190af7301f824615e88 |
completed | May 3, 2026, 8 a.m. |
| PD | Predicate disambiguation | batch_69f6fc53f4f881908dcc698687bbb64d |
completed | May 3, 2026, 7:42 a.m. |
| PDg | Predicate description generation | batch_69f6ffb7554881908993d6d2ffbcf8f5 |
completed | May 3, 2026, 7:56 a.m. |
Created at: April 29, 2026, 7:32 p.m.