Triple
T97098
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Delaware North |
E1955
|
entity |
| Predicate | hasKeyActivity |
P4153
|
FINISHED |
| Object | food and beverage concessions |
—
|
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: food and beverage concessions | Statement: [Delaware North, hasKeyActivity, food and beverage concessions]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasKeyActivity Context triple: [Delaware North, hasKeyActivity, food and beverage concessions]
-
A.
hasMissionActivity
Indicates that an entity is associated with, performs, or is involved in a specific mission-related activity.
-
B.
hasKeyEvent
Indicates that an entity includes, is associated with, or is characterized by a significant or defining event.
-
C.
hasKeyFigure
Indicates that an entity includes, involves, or is characterized by an important or central person relevant to it.
-
D.
hasKeyBattle
Indicates that an entity is associated with a major or decisive battle that is central to its history, role, or significance.
-
E.
hasKeyDocument
Indicates that an entity possesses or is associated with a primary or essential document relevant to a particular context or process.
- 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_69a24d4862f881908cc8b89d3a78031d |
completed | Feb. 28, 2026, 2:04 a.m. |
| NER | Named-entity recognition | batch_69a250cb400c8190b56343bbe19b48c7 |
completed | Feb. 28, 2026, 2:19 a.m. |
| PD | Predicate disambiguation | batch_69a24ebd19c48190bab291fea0ecc0c2 |
completed | Feb. 28, 2026, 2:11 a.m. |
| PDg | Predicate description generation | batch_69a250ca7eec8190b31f7e61f5e3ee1f |
completed | Feb. 28, 2026, 2:19 a.m. |
Created at: Feb. 28, 2026, 2:09 a.m.