Triple
T17681565
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Extended Essay |
E440782
|
entity |
| Predicate | minimumWordCount |
P7605
|
FINISHED |
| Object | 3500 words (recommended) |
—
|
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: 3500 words (recommended) | Statement: [Extended Essay, minimumWordCount, 3500 words (recommended)]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: minimumWordCount Context triple: [Extended Essay, minimumWordCount, 3500 words (recommended)]
-
A.
minimumTerm
Indicates the shortest or least duration, period, or term that must apply within a given relationship or agreement.
-
B.
wordLength
Indicates that there is a relationship specifying the number of characters (length) in a given word.
-
C.
wordCount
chosen
Indicates the total number of words contained in a given text or linguistic unit.
-
D.
sentenceLength
Indicates the length or number of units (such as characters, words, or tokens) that a given sentence contains.
-
E.
minimumNumberOfMembers
Indicates the smallest allowable or required number of members that must be present or involved in a given context or group.
- 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_69d8b9e940b081908b862bb0e6e89b0d |
completed | April 10, 2026, 8:50 a.m. |
| NER | Named-entity recognition | batch_69e470445b3881908bb0930b986089f7 |
completed | April 19, 2026, 6:03 a.m. |
| PD | Predicate disambiguation | batch_69e3cde3673c8190a889e14ba1f07dc1 |
completed | April 18, 2026, 6:30 p.m. |
Created at: April 10, 2026, 10:01 a.m.