Triple
T20416491
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Love's Labour's Won |
E500725
|
entity |
| Predicate | hasTextualStatus |
P12717
|
FINISHED |
| Object | no known surviving text |
—
|
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: no known surviving text | Statement: [Love's Labour's Won, hasTextualStatus, no known surviving text]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasTextualStatus Context triple: [Love's Labour's Won, hasTextualStatus, no known surviving text]
-
A.
hasStatusInText
Indicates that a particular status or state is explicitly mentioned or described within a given text.
-
B.
hasTextualCharacter
Indicates that something possesses or exhibits the qualities of written or printed text, such as letters, symbols, or characters.
-
C.
statusInText
Indicates that the text explicitly states or conveys the status or condition of an entity.
-
D.
hasText
Indicates that an entity is associated with or contains a specific piece of textual content.
-
E.
hasStatusLabel
chosen
Indicates that an entity is associated with a specific status expressed as a human-readable label.
- 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_69e0b4a935588190b9446a99b37ced44 |
completed | April 16, 2026, 10:06 a.m. |
| NER | Named-entity recognition | batch_69e67a4437448190b07b6e6e3de5830f |
completed | April 20, 2026, 7:11 p.m. |
| PD | Predicate disambiguation | batch_69e5766df0008190a73c4f613c29678f |
completed | April 20, 2026, 12:42 a.m. |
Created at: April 16, 2026, 11:30 a.m.