Triple
T37464713
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Dragonqueen Alexstrasza |
E931004
|
entity |
| Predicate | cardTextFlavor |
P187898
|
FINISHED |
| Object | She’s got a plan for the whole family. |
—
|
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: She’s got a plan for the whole family. | Statement: [Dragonqueen Alexstrasza, cardTextFlavor, She’s got a plan for the whole family.]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: cardTextFlavor Context triple: [Dragonqueen Alexstrasza, cardTextFlavor, She’s got a plan for the whole family.]
-
A.
cardText
Indicates that one entity is the textual content displayed on a card associated with another entity.
-
B.
hasFlavorText
Indicates that an entity is associated with descriptive or thematic text intended to provide additional narrative or atmospheric detail.
-
C.
cardTextType
Indicates the type or category of textual content associated with a card (e.g., title, body text, caption, or label).
-
D.
flavorText
chosen
Indicates that one entity provides descriptive or atmospheric text associated with another entity, typically for display or narrative purposes.
-
E.
cardColor
Indicates the color attribute assigned to a card in the relationship.
- 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_69f76ec1a1148190b0a961f188d621b0 |
completed | May 3, 2026, 3:50 p.m. |
| NER | Named-entity recognition | batch_69fce7671f108190bf3ebf54339068b5 |
completed | May 7, 2026, 7:26 p.m. |
| PD | Predicate disambiguation | batch_69fce5b5a84c81908ac1b5b9f08d48d0 |
completed | May 7, 2026, 7:19 p.m. |
Created at: May 3, 2026, 4:17 p.m.