Triple
T10156759
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Transfer-Encoding header field |
E233793
|
entity |
| Predicate | hasTokenType |
P33731
|
FINISHED |
| Object | transfer-coding |
—
|
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: transfer-coding | Statement: [Transfer-Encoding header field, hasTokenType, transfer-coding]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasTokenType Context triple: [Transfer-Encoding header field, hasTokenType, transfer-coding]
-
A.
tokenType
chosen
Indicates the classification or category assigned to a token within a sequence, such as its syntactic, semantic, or functional role.
-
B.
haveType
Indicates that an entity belongs to or is classified under a specified type or category.
-
C.
hasKeyType
Indicates that an entity possesses or is associated with a specific category or type of key.
-
D.
hasCurrentType
Indicates that an entity currently possesses or is classified under a specific type or category, as opposed to past or potential types.
-
E.
hasNodeType
Indicates that an entity is associated with, or classified as, a specific type of node within a structured system or model.
- 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_69ca848e80748190b91d1e04d35512c7 |
completed | March 30, 2026, 2:11 p.m. |
| NER | Named-entity recognition | batch_69cdec3c47dc81909679903e6024eb49 |
completed | April 2, 2026, 4:10 a.m. |
| PD | Predicate disambiguation | batch_69cd4ba795808190acc9124c98c6e40f |
completed | April 1, 2026, 4:45 p.m. |
Created at: March 30, 2026, 9:09 p.m.